Flow builder

In this section anything you need to know about building a flow

[Flow builder overview](/2b7a4a48df2980ae8e5afd54df5ae4f3)


[Sub flows](/2c3a4a48df2980139cafd825209043ae)


[analytic](/2b7a4a48df2980ce8f60fee4fed512bc)


[Live chat ](/2c3a4a48df2980f383edc89a379c05e0)


[Bot user](/2c4a4a48df2980008d76f9ddf53ca28f)


[AI Hub](/2c4a4a48df29802a98dfd8940140251c)


[Automation](/2e0a4a48df29808dbb78dda87f181bdd)


[Content](/2e0a4a48df2980ed8701d11e0d724a8b)


[Tools](/2e2a4a48df2980f38c6afd131da83251)


[Broadcast](/2e3a4a48df29804dadeed8bec327a557)


[Settings](/2e3a4a48df2980ffbb7fc4bdd657c105)

If you want more precision about building blocks (send nodes, quesiton nodes, action nodes,…) please refer to the next section building blocks & steps

Flow builder overview

This section will give you an overall idea about how to use the UChat flow builder. You can open a flow and try side by side when you learn it.

💡 IMPORTANT - 💁 Please make sure you go through every detail on this page before you start building bots.

Channels, Sub Flow and Step

Channels

To begin with, you need to create a channel. Currently, Messagingme.app provides you with 17 types of channels:

Facebook

Instagram

Whatsapp Cloud

Tiktok

Slack

WeChat

SMS

RCS

Voice

Line

Viber

Intercom

JivoChat

ChatWoot

SubFlow type

Flow consists of sub flows. There are 3 types of sub flow:

Sub Flow Type - General flow for sending messages and other user interactions, most common type of flow used in automations

Function Flow - Used for processing repetitive tasks

Workflow - Used for processing background tasks and tasks that neccesarily dont need user interaction

Step type

Sub Flow consists of steps. There are 8 types of steps:

💡 The differences among different types of flow are Flow Setup, Send Message Step and Question Step. Each channel has its own limitation of message types. For example, you can display a product gallery in Facebook Messenger while the SMS channel doesn’t support that.

Flow labels

Flow Labels are designed to help users label and organize sub-flows within their Flow Builder. Each label is customizable with its own name and color, making it easier to visually distinguish different flow types.

This feature is especially useful for those managing multiple sub-flows, offering quick identification and filtering options to streamline workflow management.

Creating a Label and Assigning Color

To create a label:

Go to the Flow Builder.
Enter the label’s name.
Choose a color for the label.

By assigning labels with different colors, organizing sub-flows becomes effortless. You can easily spot and manage them based on their assigned categories.

Adding a Sub-Flow to a Label

Adding a sub-flow to a label is simple:

Click on the vertical ellipsis (three dots) next to the sub-flow.
Select Manage Labels from the dropdown menu.
Add the sub-flow to your desired label.

By assigning labels with different colors, organizing sub-flows becomes effortless. You can easily spot and manage them based on their assigned categories.

Adding a Sub-Flow to a Label

Adding a sub-flow to a label is simple:

Click on the vertical ellipsis (three dots) next to the sub-flow.
Select Manage Labels from the dropdown menu.
Add the sub-flow to your desired label.

This process ensures that your sub-flows are neatly categorized under the appropriate labels.

Accessing Sub-Flows by Labels

When it comes to filtering sub-flows by labels, you have two options:

All Selected Labels: This filter will display only the sub-flows that contain all of the labels you select.

2 Any Selected Labels: This option shows all sub-flows that have at least one of the selected labels.

Managing Sub-Flows in Folders with Flow Labels

When you first access your flows, all flows are displayed, including those inside folders and the Root directory.

Once you apply a label filter:

Only the sub-flows that match the selected labels will be visible.
The unselected flows, both in the Root directory and inside folders, will be hidden from view.

When you open a specific folder after applying a label filter:

Only the sub-flows with the chosen labels will be visible inside that folder.
All other sub-flows that do not match the label filter will remain hidden, even if they exist within the same folder.

Bulk Actions for Flow Label Management

Flow Labels also offer bulk management capabilities. You can now:

Add or remove labels from multiple sub-flows at once
Move them into folders
Even delete sub-flows in bulk.

Field

Field, aka variable, is a container to hold a value.

Classification	Description
system field and custom field	system field is created by the system with pre-defined variable name and type, while custom field is defined by yourself
bot field and user field	bot field is shared in the whole bot, while each user has his/her own set of user fields
text field, number field, boolean field, date field, datetime field and JSON field	see variable type

User field

User field belongs to users. For example, each user has their own name and email address. So “name” and “email” are user fields.

Bot field

Bot field belongs to the bot. For example, a restaurant bot holds an address and contact number of the restaurant. So “restaurant_address” and “restaurant_contact” should be created as bot fields. Because you don’t want to manage different addresses or contacts of your restaurant for every user.

System field

System field is created by the system with pre-defined variable name and variable type. There are system bot field and system user field:

Field Name	Field Name	Field Name	Field Name	Field Name
User Ns	user field	text	user identification in MM	non-editable
User Id*	user field	text	user identification from the channel	non-editable
First Name	user field	text	profile info	in Question Step/Action Step
Last Name	user field	text	profile info	in Question Step/Action Step
User Name	user field	text	profile info	in Action Step
Gender	user field	text	profile info	in Action Step
Email	user field	text	profile info	in Question Step/Action Step
Phone	user field	text	profile info	in Question Step/Action Step
Profile Image	user field	text	profile info	in Question Step
Locale	user field	text	profile info	non-editable
Timezone	user field	text	profile info	non-editable
Language	user field	text	profile info	in Action Step
Subscribed	user field	datetime	subscribed time	non-editable
Last Text Input	user field	text	user’s last input	edited by system
Last Interaction	user field	datetime	last action time	edited by system
Last Button Title	user field	text	last button pressed	edited by system
Flow Ns	bot field	text	flow(bot) identification in MM	non-editable
Sub Flow Ns	bot field	text	sub flow identification in MM	non-editable
Page Name	bot field	text	connected Facebook page name	non-editable
Page Id	bot field	text	connected Facebook page id	non-editable
Page User Name	bot field	text	username of the page in Facebook	non-editable
Last FB Comment	user field	text	user’s last comment text in the Facebook page	edit by system
Last FB Comment Post Id	user field	text	post id of where user put the last comment	edit by system
Last FB Comment total tagged users	user field	number	tagged users amount in last comment	edit by system
Last FB Comment total new tagged users	user field	number	tagged but haven’t subscribed(to bot) users amount	edit by system
Last FB Comment is existing users	user field	number	before this comment, is he/she an existing user? yes=1,no=0	edit by system
Live Chat Url	user field	text	(for agent) visit to talk to user in live chat	edit by system
NOW	user field	datetime	current time in user’s timezone*	edited by system
TODAY	user field	date	current date in user’s timezone*	edited by system
BOT_CURRENT_TIME	bot field	datetime	current datetime in workspace’s timezone	edited by system
ITEM	user field	array (JSON)	each item in a JSON	in “For Each” message
SELECT	user field	array (JSON)	selected item	in “Select” new step
SHOP	bot field	array (JSON)	store information	in Ecommerce Integration
CART	user field	array (JSON)	user shopping cart	in Action Step
ORDER	user field	array (JSON)	user’s last order	edited by system
User	user field	array (JSON)	user’s profile	edited by system according to other profile values
DialogFlow	user field	array (JSON)	DialogFlow response	edited by DialogFlow agent

💡 Note - If the channel doesn’t support timezone in user’s profile, or, the channel supports but the user don’t have a timezone value, workspace timezone will be used instead.

User Id in Different Channels:

Channel	Meaning	Example Value
Facebook	Unique Id in your Facebook page	6288386817841812
Instagram	Unique Id in your Instagram bot	6570462892993643
Telegram	Unique Id in your Telegram bot	1173717756
Slack	Unique Id in your Slack workspace	U017MKNENH
WeChat	Unique Id in your WeChat account	oNzS3wpEjnA3tXmOcNxpqtAnBwWg
WhatsApp	User’s phone number without +	61412345678
SMS	User’s phone number	+61412345678
Voice	User’s phone number	+61412345678
Google	Conversation Id from Google	8095938e-90cf-4347-ab94-9224308672b0
Line	Unique Id in your Line bot	Ub02c77c69c59c5be5597d58ce2701ebe
Viber	Unique Id in your Viber bot	mdY9hOWdeQC6J/Sl19Qh8A==
Vk	Unique Id in your Vk bot	705862439

💡 Note - The unique id from the channel is only unique in your Facebook page, Telegram bot, Slack workspace or WeChat account, not the unique id in the whole Facebook, Slack, etc.

Variable Type

There are 6 types of variable in MessagingMe.app :

Type	Storage	Example	Operations Supported
Text	letters, words, sentences…	Hi, UChat.	cutting, change case, encode, decode…
Number	numbers	123.45	+ - x ÷, mod, power, log, root, round…
Boolean	either “1” or “0”, for true or false	1	assign
Date	date	2021-03-30	format, add months/weeks/days
DateTime	date and time	2022-01-01T12:00:00+10:00	format, add months/weeks/days/hours/minutes
JSON (array)	a series of variables	{“name”:“Jack”, “age”:“20”}	load, get, update, remove, count, sum, average, sort, shuffle, reverse…

Boolean Value

When these values stored in the field, the boolean return false, otherwise it goes true:

empty
null
‘false’
false
‘no’
0

Create Custom Field

Wow, now you are a master 👨‍🎓 of field! Let’s try it out! 😎😎

You can create variables in 2 ways:

Place	Type Supported
in Contents section	user field & bot field
anywhere you need to map result to variable, e.g. Question step, Integration, etc	user field only

Create Custom Field in Contents Section

go “Contents” from the left sidebar
select User Fields or Bot Fields
use folder to organize your fields if needed

Click the blue ”+ New User/Bot Field” button on the right side to create a field. “Field Name” is a must. You can use any character to separate words like underline or space. We suggest you keep the field name as concise as possible, to avoid any possible display issue.

After that, pick a variable type. Add default value or description if needed. (default value is for bot fields only)

Folders can be used to organize variables. Trust me, you will need it when your flow goes big. 🧐

Create Custom Field in Question and Action Step

To create new fields in for example, the question step:

Type in a new variable name in the “Enter Field Name” box and click it in the drop-down list. Select correspond variable type and here you go.

Another example, create in an integration:

Publish Version & Draft Version

In MessagingMe.app, each flow has a Publish Version and a Draft Version.

Publish Version

your bot talk to clients using the publish version.
Draft Version

any editing of steps will be saved automatically to the draft version. you can edit your flow without influencing the bot and test the draft version before you “Publish”.

From Publish Version to Draft Version, 1 way:

Click “Edit Flow” on the upper left/right corner of the flow to enter the draft version

From Draft Version to Publish Version, 3 ways:

click “Publish” to save your draft to a new Publish Version
discard changes and revert to the newest Publish Version
keep draft and switch to Publish Version (by doing this, you can have a look at your publish version and when you click edit and come back, your draft is still here)

💡 Don’t worry if you accidentally quit during your editing, the system will keep all your modifications in Draft Version. So when you come back, simply enter Draft Version again and you can see your modifications remain intact.

💡 TIP - You might want to create a flow first, then open the flow side by side when you read the following instruction (Facebook flow used as an example).

After entering a flow, this is what you will see:

On the top, there is a navigation bar. From left to right there are:

Part	Usage
”Demo Account”	current workspace, click to go back to UChat dashboard
”Support”	flow type and flow name, click to go back to “All Bots"
"Main Flow”	current sub flow
”Preview”	preview the current subflow from the Start Step
”Build a bot…“	tutorial video widget
”Joyce”	current user, click for user settings, support and logout

💡 Preview Feature - Please note that “Preview” feature is not supported in all channels. Channels support “Preview”: Facebook, Telegram, WhatsApp, Line and Viber. For channels without Preview, search “talk to bot” in the documentation.

On the left-hand side, there is a sidebar. From top to bottom there are:

Section	Usage
Flow Builder	build subflows here
Flows	manage all your subflows
Analytics	bot data analysis
Live Chat	inbox for all the conversations, make a human reply here
Bot Users	manage bot user profile. import, export, search or delete bot users
Automation	manage keywords, sequences, triggers and comments
Contents	manage custom fields, tags, OTN, personas, user menus and customer feedback
Tools	manage error logs, draft version tester, bot admins, widgets, multiple language and shortcuts, Facebook Ads, inbound webhooks
Broadcasts	send/manage broadcasts
Settings	(some are owner only) manage bot users limit, Facebook greeting text, chat widget customization, ice breakers and authorized websites

💡 Note - Features in Automation, Contents, Tools and Settings can be different from channel to channel. In Settings, usually owner can see all the settings like bot user limit while admin and member only see part of them

Flow Builder

Apart from those in the above screenshot, there are a couple of more tips for using the flow builder:

Change Themes

Before you start, you can pick your favourite theme by clicking “Change Theme”:

choose one of them and “Apply Change”.

Hide Mini-map or Tooltips

Mini-map is useful when you need to move your workspace in some situations. For example, when you click and drag inside a canvas, you are moving the canvas as a whole instead of everything in the builder:

You can hide the mini-map by clicking the “Hide Flow Overview” option.

With tooltip, you can see description for every feature you see in the flow builder like this:

The tooltip includes a title, description, image, video link and documentation link. It is friendly to new users. For users who are already familiar with the system, you can choose to disable the tooltip by clicking the “Hide Flow Tooltips” option.

Basic Operations to Build Flows

Edit step

Click on a step to edit it, “Edit Panel” will show next to the sidebar.

Click step name to edit it. You can choose the next step at the bottom of the edit panel or drag connectors from the circle to the tile of another step.

Connect Steps:

Create a new step or choose an existing one to be the next step. For dragging connectors, see below:

💡 When you choose an existing next step, a line will be connected from the current step to the next. Too many lines can be messy, get a Goto step to help you organize! In a Goto step, you can nominate the next step without creating a line connector.

Select Multiple Steps (Move to Canvas/Sub Flow)

We’ve just learned how to move the builder by clicking and dragging. For selecting multiple steps, it’s a bit similar. Hold the Shift key then click and drag to cover the steps you would like to select:

Alternatively, ctrl + click them one by one:

The selected step has a green border. After selecting multiple steps, click “Create New Canvas” to organize these steps in a canvas box, or move them to an existing sub flow. To delete multiple steps, hit the “delete” button on your keyboard after choosing several steps:

💡 Delete on Mac - On Mac OS computer, hold fn and hit Delete to remove steps. Or use the “Delete Selected button in the editing panel.

💡 TIP - The green start point is the entrance of a sub flow. It can’t be moved to other sub flows or deleted even you include it in a group of steps.

Copy and Paste Steps

After you select a step or multiple steps, use Ctrl + C to copy and Ctrl + V to paste it to:

the same subflow
different subflows in the same bot/flow
different bots/flows but the same channels (associate custom fields will be created automatically)
different channels (unsupported features will be removed)

💡 TIP - Please note that you can only paste ONCE. Copy again for another paste. This is to prevent bulk pasting which can quickly blow up the flow.

Sub Flows

UChat offer 3 different type of flows.

Flow Type	Description
Normal Subflow	Varies in channels, basic subflow
Workflow	work at the backend without influencing the front end task
Function Flow	perform repetitive tasks

Workflow

Workflow is better for running some actions in background process, such as sending data to external request for tracking, which may take a few seconds to complete, and the response is not required for the next message sent to bot user.

You will not be able to use any send message or ask questions to bot user inside workflow.

A workflow can be considered as a backend flow where you can automate tasks such as adding or removing tags, set custom field variables, do external API calls.

This way the conversation you have with the subscriber will not be affected by needing to wait to apply all those actions and the experience is as smooth as possible for that end-user.

Create Workflow

To create a workflow just go to the flow overview by selecting Flows from the left-hand menu.

Then press the button + New Sub Flow

Select the workflow flow type then give it a name. Once done press the button Create to start creating your workflow.

Once you create your flow and you end up in the flow builder you will notice that you will have access to fewer blocks than when selecting a regular or function flow.

Available blocks are:

Action
Condition
Split
Send Email

As mentioned this flow is meant to create a backend flow that you can trigger from any other flow inside your chatbot to handle system tasks like adding tags, set custom fields, but also sending emails.

Workflow Example

Let’s take an example of how a workflow can be used.

A user signs up with an email and or phone number and you want to sync this information with your CRM platform of choice.

So soon as you grabbed the credentials from the user you can make an API call using the external request block inside of the action module.

You would also want to tag the user inside the chatbot for completing the onboarding step. After done we send an email notification to an admin that a new lead has been created to follow up on.

A workflow can then look something like this

If you were to incorporate this into the flow that has the actual conversation it might become an issue as the conversation could be on hold for several seconds or more to finish all these system processes. And you might lose the user as he or she thinks the conversation is done.

Trigger Workflow

It is very simple to trigger the above workflow inside of any other flow that you build.

Just insert an action block, go to advanced actions, then choose trigger workflow at the bottom

You can then select any workflow you created. This workflow will then be processed in the backend while the conversation with the user will not be affected and continue without any delay.

Function flow

Function flow is better for reusable flow, which handles the common logic and returns back the results via output node. For example, you can use it to check the business hours and then route to different output based on the business hours.

also you can check if user has specific tag or not, and then you may follow up to different questions based on result. The key benefit is if you have may sub flows need to handle similar logic, then by using the function flow, you will be able to manage the logic from one single flow, it is easy to maintain and make changes.

A function flow is a fantastic way of preventing you to create repetitive flows over and over again. Think of when you need ask for emails or phone numbers.

With a function flow you will be able to send the user to that one flow, then once completed the user can continue exactly from the point they left off in the previous flow.

Create Function Flow

To create a function flow go to Flows from your left-hand menu, then press the button + New Sub Flow.

Select the Function flow type and name your flow. Once done press the button Create and you will be taken to the flow builder.

Function Flow Example

Once inside the flow builder and wanting to insert a new block you will see that you have all the blocks at your disposal just like in a regular flow, and one extra called Output.

This output is what makes this function flow so unique as it gives you the ability to send the user back to the previous flow (if you like) exactly where he or she left off.

Let’s create an example where we ask the user for an email and add an output module to it;

As you can see a simple flow but with the benefit this is the only function of the flow, asking for an email.

Call Function Flow

After this flow is finished you can return the user to the previous flow to continue the conversation there if you like.

Let us show you how that could look like;

There are many use cases for function flows so you can get as creative as you like.

Multiple Outputs

Multiple Output Steps are supported in your Function Flow.

When you call a Function Flow with multiple outputs, the titles of those outputs will show in the Goto Step and you can handle it accordingly.

Analytic

Message Reports

This report provides detailed information about the volume of messages sent and received in your channel, allowing you to monitor user activity and engagement over time.

Steps to Access

Within your bot, go to Analytics.

Select Messages from the left-side menu.

Available Report Types

Messages

Analysis of Received and Sent Messages

This section details the metrics of received and sent messages over a specific period. The charts help visualize the fluctuations in communication and compare them to previous periods.

Line Charts

Received Messages:

The orange line represents the received messages in the current period.
The gray line represents the received messages in the previous period.

Sent Messages:

The blue line represents the sent messages in the current period.
The gray line represents the sent messages in the previous period.

Usefulness of the Charts

Volume Analysis: Helps understand the volume of communication on different days, identifying patterns of high and low activity.
Performance Evaluation: Assists in evaluating the effectiveness of responses and engagement with users.
Period Comparison: Comparative visualization between different periods helps identify trends and potential areas for improvement.

Below is a visual example of the charts:

Analysis of Agent Messages, Private Notes, and Emails

This section provides a detailed overview of agent messages, private notes, and emails sent and opened during a specific period. The charts allow for a clear comparison between the current and previous periods, helping to assess performance and identify trends.

Agent Messages

Line Chart:
- The green line represents agent messages in the current period.
- The gray line represents agent messages in the previous period.

Private Notes

Line Chart:
- The blue line represents private notes in the current period.
- The gray line represents private notes in the previous period.

Emails Sent

Line Chart:
- The light blue line represents emails sent in the current period.
- The gray line represents emails sent in the previous period.

Emails Opened

Line Chart:
- The orange line represents emails opened in the current period.
- The gray line represents emails opened in the previous period.

Usefulness of the Charts

Performance Evaluation: The charts help understand the efficiency of agent communication and the use of private notes.
Email Analysis: Allows evaluation of reach and engagement through sent and opened emails.
Trend Identification: Comparing periods helps identify changes and make informed decisions.

Below is a visual example of the charts:

Conversations

Conversation Overview

The number of new conversations started, the number of unique conversations that were first closed, and the number of unique conversations that were reopened

This section provides an overview of conversations over a specific period. The chart helps visualize the number of new, closed, and reopened conversations, facilitating the analysis of customer support activity and efficiency.

New Conversations: Represented in blue, these are the conversations initiated by users during the period.
Closed Conversations: Represented in green, these are the conversations that were closed during the period.
Reopened Conversations: Represented in red, these are the conversations that were reopened after being closed.

Usefulness of the Chart

Support Efficiency: By comparing the numbers of new, closed, and reopened conversations, it is possible to evaluate the support team’s efficiency and identify areas needing improvement.
Activity Peaks Identification: The chart shows the days with the highest and lowest activity, allowing for resource allocation adjustments to improve support during peak times.

Below is a visual example of the chart:

Opened vs. Closed Conversations

The number of conversations opened and the number of conversations that were closed

This section presents a comparison between the number of open and closed conversations over a specific period. The chart helps visualize customer support efficiency and identify potential bottlenecks or periods of high demand.

Opened Conversations: Represented in blue, these are the conversations initiated by users during the period.
Closed Conversations: Represented in green, these are the conversations that were closed during the period.

Usefulness of the Chart

Support Efficiency: By comparing the numbers of open and closed conversations, it is possible to evaluate the support team’s efficiency. Ideally, the number of closed conversations should be close to the number of open conversations.
Activity Peaks Identification: The chart shows the days with the highest and lowest activity, allowing for resource allocation adjustments to improve support during peak times.

Below is a visual example of the chart:

Heatmap of Opened and Closed Conversations

The conversations opened volume by day of the week and time of day.

In this section, we present heatmaps showing open and closed conversations throughout the week, segmented by hour of the day. These charts help identify activity patterns, allowing for optimized resource allocation and support planning.

Heatmap of Opened Conversations

The chart on the left shows open conversations by day of the week and hour of the day. Darker colors indicate periods of higher activity.
This heatmap is useful for identifying when users are most likely to initiate conversations, allowing for adjustments in the support team to cover peak times.

Heatmap of Closed Conversations

The chart on the right shows closed conversations by day of the week and hour of the day. Similar to the heatmap of open conversations, darker colors indicate higher activity.
This chart helps understand customer support efficiency and whether there are periods when conversations are closed more quickly.

Below is a visual example of these charts:

Opened Conversations by Type

In this section, we present an analysis of open conversations categorized by type. This metric is essential for understanding the dynamics of interactions, distinguishing between new users and returning users.

Opened Conversations by New and Returning Users

The bar chart shows the number of open conversations by new users and returning users over the days. This helps us monitor how different types of users are interacting with the system.
The donut chart on the right presents the overall proportion of open conversations by new and returning users, offering a clear view of the distribution of interactions.

Below is a visual example of these charts:

Closed Conversations by Type

In this section, we present an analysis of closed conversations categorized by type. This metric is important for understanding customer behavior and support efficiency.

New and Returning Closed Conversations

The bar chart shows the number of new and returning conversations that were closed over the days. This helps us monitor how customers are interacting with support over time.
The donut chart on the right presents the overall proportion of new versus returning closed conversations, offering a clear view of the distribution of closed interactions.

Below is a visual example of these charts:

Open Conversations by Source

Bot user means bot user/contacts initiated, Agent means live chat agent, Bot means bot automation.

In this section, we present an analysis of open conversations categorized by source. This metric is essential for understanding the origin of interactions and evaluating the effectiveness of different support channels.

Open Conversations by Bot Users, Agents, and Bot

Bot user means bot user/contacts initiated, Agent means live chat agent, Bot means bot automation.
The bar chart shows the number of open conversations by bot users, agents, and the bot itself over the days. This helps us monitor how different channels are being utilized over time.
The donut chart on the right presents the overall proportion of open conversations by each source, offering a clear view of the distribution of initiated interactions.

Below is a visual example of these charts:

Conversations and Conversation Closures

In this section, we provide an overview of the number of conversations and how they were closed, either by an agent or a bot. Analyzing these metrics can help us better understand customer interaction with our support system.

New and Returning Conversations

The bar chart at the top shows the number of new and returning conversations over the days. It is important to track this metric to understand the flow of interactions and customer loyalty to the support system.
The donut chart on the right presents the overall proportion of new versus returning conversations, offering a clear view of the distribution.

Closed Conversations by Source

The second bar chart illustrates the number of conversations closed by agents and bots over time. Monitoring this information helps identify the efficiency of each source in closing cases.
The donut chart on the right presents the overall proportion of conversations closed by agents and bots, providing an overview of each one’s performance.

Below is a visual example of these charts:

Response

Average First Response Time

The average time taken for the first agent to send the first response from the time when the conversation is first time opened, only calculate the time within the office hours

This metric measures the average time it takes for an agent to respond to a request for the first time, providing a critical view of how quickly the support team is initially responding to customers.

Average First Response Time

The line chart shows the average first response time over a period. Monitoring this metric is crucial for evaluating the initial efficiency of the support team and identifying areas that need improvement.

First Response Time Breakdown

This bar chart presents the distribution of first response times across different time intervals, allowing for a more detailed analysis of the speed of first responses and helping to identify potential bottlenecks.

Below is a visual example of these charts:

Average Time from First Assignment to First Response

The average time taken for the first agent to send the first response from the time when the conversation is first assigned, only calculate the time within the office hours

This metric measures the time from the first assignment of a case to the agent’s first response, helping to evaluate the initial efficiency in responding to customers.

Average Time from First Assignment to First Response

The line chart shows the average time it takes for agents to respond from the first assignment of a case. Monitoring this metric is essential to ensure a quick and efficient response to customers from the beginning of the interaction.

First Assignment Response Time Breakdown

This bar chart presents the distribution of response times across different time intervals, providing a detailed view of the speed of first responses and identifying areas for improvement.

Below is a visual example of these charts:

Average Time from Last Assignment to Response

The average time taken for the last assignee to send the first response from the time when the conversation is last assigned, only calculate the time within the office hours

This metric helps evaluate the efficiency of the final response from agents after the last assignment, which is crucial for ensuring customer requests are completed quickly.

Average Time from Last Assignment to Response

The line chart presents the average time agents take to respond after the last assignment. Monitoring this metric helps us understand how quickly we are resolving the final issues for customers.

Last Assignment Response Time Breakdown

This bar chart shows the distribution of final response times across different time intervals, providing a detailed view of how response times vary and where improvements can be made.

Below is a visual example of these charts:

Average Response Time

The average time taken to respond to the incoming message from the contact by all assignees, only calculate the time within the office hours

This metric is crucial for evaluating how quickly agents respond to customer messages, helping to measure the efficiency of our customer service.

Average Response Time

This line chart shows the average response time of agents for each customer interaction. Monitoring this metric allows us to identify if agents are responding promptly to customer requests.

Response Time Breakdown

This bar chart illustrates the distribution of response times across different time intervals. It provides a clear view of how quickly agents are responding, enabling us to identify areas needing improvement.

Below is a visual example of these charts:

Average Subsequent Response Time and Average Number of Responses

The average time taken for any agents to respond to contacts for every subsequent reply after the first reply, only calculate the time within the office hours

These metrics are essential for understanding the efficiency and quality of our customer service, particularly in the continuity and number of interactions needed to resolve an issue.

For example, if the user send the message at 00:00, and then the live chat agent replied to this message at 01:00, and then the first response time will be 1 minutes, but the agent send another subsequent message to the user at 03:00, and then the subsequent response time will be 2 minutes.

Average Subsequent Response Time

This line graph shows the average time between subsequent responses after the first interaction. Monitoring this metric helps identify if agents are responding promptly to customers during ongoing conversations.
Subsequent Response Time Breakdown: This bar chart illustrates the distribution of subsequent response times in different time intervals. It helps visualize how quickly agents are responding after the first response.

Average Number of Responses

This line graph shows the average number of responses needed to resolve a conversation. A lower number of responses may indicate a more efficient and clear resolution of customer issues.
Response Breakdown: This bar chart shows the distribution of the number of responses per conversation. It helps identify how many interactions are frequently needed to resolve a conversation.

Below is a visual example of these graphs:

Definition of Agent Response Time

1. Understanding the Context

There are three message types:

TYPE_USER_IN → user sends a message (customer).
TYPE_BOT_OUT → bot replies.
TYPE_AGENT_OUT → live agent replies.

Agents may join mid-conversation, where the bot is already replying automatically. When the agent replies, the bot pauses temporarily.

The goal is to measure:

“How long it takes an agent to respond to a user’s message that needs human attention.”

🧩 2. Core Definition of Agent Response Time

Agent Response Time (ART) =

The time difference between the user’s last message that requires a human response and the agent’s first outgoing message after that.

However, since a bot might respond automatically before the agent takes over, we need to ignore bot messages when computing ART.

That means:

Only measure from the user’s message (TYPE_USER_IN)
To the next agent reply (TYPE_AGENT_OUT)
While ignoring intermediate bot messages (TYPE_BOT_OUT)

🧠 3. Rules for Accurate Measurement

Case	Description	Should Count as Response Time?
User sends message → Agent replies directly	Standard case	✅ Yes
User sends message → Bot replies → Agent later joins	Agent took over after bot	✅ Yes (start from user message, not bot)
Bot sends proactive message → Agent replies	No user message triggered it	❌ No
Agent replies to another agent	Internal collaboration	❌ No
Agent replies after user message but after a long gap (bot paused, waiting for agent)	Still counts	✅ Yes
User sends multiple messages before agent replies	Use the last user message before the agent reply	✅ Yes

4. Algorithm / Logic Flow

You can calculate the agent response time like this:

For each TYPE_AGENT_OUT message:
- Look backward in time for the most recent TYPE_USER_IN message.
- Ignore any TYPE_BOT_OUT or TYPE_AGENT_OUT messages in between.
- Compute the time difference:ART = agent_out.timestamp - user_in.timestamp
Exclude:
- If there is no prior TYPE_USER_IN.
- If the last message before agent reply was another agent message.
- If the agent message is part of a rapid sequence (same agent continuing conversation).

💡 If the agent sends multiple messages in a row, only the first message after the user input counts as a “response.”

Resolutions

Average Resolution Time

💡 The average time taken for the first agent to send the first response from the time when the conversation is first time opened, only calculate the time within the office hours

The Average Resolution Time is a crucial metric that helps us assess the efficiency of our customer service process. This metric indicates the average time it takes to resolve and close a conversation. Below are the details of this metric:

Average Resolution Time

This line chart shows the average time it takes to resolve a conversation from start to finish. Monitoring this metric allows us to identify trends and possible delays in the resolution process, helping us implement continuous improvements.

Resolution Time Breakdown

This bar chart shows the distribution of resolution times across different time intervals. It helps us understand how long conversations take to be resolved and whether there are specific patterns that can be optimized for more efficient service.

Below is a visual example of these charts:

Average Time from First Assignment to Closure

💡 The average time taken for first time close a conversation from the time when the conversation is first assigned, only calculate the time within the office hours

To monitor the efficiency of our resolution process from the beginning, we analyze the Average Time from First Assignment to Closure. This metric helps us understand how long it takes from when a conversation is first assigned to an agent until it is resolved and closed. Below are the details of this metric:

Average Time from First Assignment to Closure

This line graph shows the average time it takes for a conversation to be closed after its first assignment. It helps us evaluate the effectiveness of the resolution process from start to finish and identify areas that may need improvement.

Breakdown of Time from First Assignment to Closure

This bar chart shows the distribution of closure times in different time intervals after the first assignment. It helps identify how quickly issues are being resolved and if there are specific steps that can be optimized for faster closure.

Below is a visual example of these graphs:

Average Time from Last Assignment to Closure

💡 The average time taken to close a conversation calculated from the time when the conversation is last assigned, only calculate the time within the office hours

To better understand the efficiency in resolving conversations, we analyze the Average Time from Last Assignment to Closure. This metric indicates how long it takes from when a conversation is last assigned to an agent until it is finally resolved and closed. Below are the details of this metric:

Average Time from Last Assignment to Closure

This line graph shows the average time it takes for a conversation to be closed after its last assignment. It helps us evaluate the effectiveness of closing conversations and identify any potential delays.

Breakdown of Time from Last Assignment to Closure

This bar chart shows the distribution of closure times in different time intervals after the last assignment. It helps identify the efficiency of the final resolution process and if there are steps that can be optimized for faster closure.

Below is a visual example of these graphs:

Average Time to First Assignment

💡 The average time taken to assign a conversation to the first assignee from the time when the conversation is opened, only calculate the time within the office hours

To monitor workflow efficiency and ensure conversations are handled promptly, we analyze the Average Time to First Assignment. This metric shows how long it takes for a conversation to be assigned to an agent after it is received. Below are the details of this metric:

Average Time to First Assignment

This line graph shows the average time it takes for a conversation to be assigned to an agent. It helps us evaluate how quickly conversations are being directed towards resolution.

Breakdown of Time to First Assignment

This bar chart shows the distribution of assignment times across different time intervals. It helps identify the efficiency of the assignment process and whether there are significant delays that need to be addressed.

Below is a visual example of these graphs:

Average Handling Time and Assignments

💡 The total amount of time that the conversation was being handled by agents. A conversation is being handled when it is assigned to any agent and has a status of Open, only calculate the time within the office hours

To further improve customer service, we monitor the Average Handling Time and the Number of Assignments until Closure. These metrics provide detailed insights into agent efficiency and workload. Below are the details of these metrics:

Average Handling Time

This line graph shows the average time an agent takes to handle a conversation from start to resolution. It is important for evaluating the efficiency of customer service and identifying areas that may need optimization.

Breakdown of Average Handling Time

This bar chart shows the distribution of handling times across different time intervals. It helps identify how long conversations typically take to be resolved, providing insights into possible improvements in the service process.

Average Number of Assignments until Closure

💡 The average number of assignments before close the conversation, Unassign also consider as one assignment count.

This line graph shows the average number of times a conversation is assigned to different agents before it is closed. This can indicate the complexity of customer issues or the need for additional agent training.

Breakdown of Number of Assignments until Closure

This bar chart shows the percentage of conversations closed after a certain number of assignments. It helps understand the efficiency of the workflow and whether adjustments are needed to reduce the number of transfers between agents.

Below is a visual example of these graphs:

LeaderBoard

Viewing Agent Performance

The agent performance dashboard in conversation mode offers a comprehensive view of your support team’s efficiency and effectiveness. Below, we detail the main elements presented:

Top Performing Agent

Displays the agent who had the best performance in the selected period, indicating the number of closed conversations.

Messages Sent

Shows the total number of messages sent by the agent or team during the period.

Assigned Conversations

Indicates the number of conversations assigned to agents.

Average First Response Time

Presents the average time agents take to respond to a new conversation.

Average Resolution Time

Displays the average time needed to resolve conversations.

Assigned Conversations Chart

A bar chart showing the number of conversations assigned to each agent.

Conversation Distribution Chart

A donut chart illustrating the percentage distribution of conversations among agents.

Below is a visual example of this dashboard:

Analysis of Closed Conversations and Messages Sent

The conversation mode also allows for the analysis of agent performance in terms of closed conversations and messages sent. Below, we detail the information presented:

Closed Conversations

A bar chart shows the number of conversations closed by each agent.
A donut chart displays the percentage distribution of closed conversations among agents, providing a clear view of who is closing the most conversations.

Messages Sent

A bar chart details the number of messages sent by each agent.
A donut chart illustrates the percentage distribution of messages sent, offering insights into the messaging activity of the agents.

These charts help identify performance patterns and the productivity of each agent, enabling better management and resource allocation.

Below is a visual example of these charts:

Average First Response Time and Average Assignment to First Response Time

The conversation mode also provides valuable insights into agent response times, focusing on the average first response time and the average assignment to first response time. Below, we detail this information:

Average First Response Time

A bar chart showing the average time each agent takes to provide the first response to a new conversation. This helps monitor how quickly agents address customers for the first time.

Average Assignment to First Response Time

A bar chart presenting the average time from when a conversation is assigned to an agent until their first response. This allows for the analysis of agent efficiency after being designated a conversation.

These charts are essential for evaluating the effectiveness of agents in responding quickly to customer inquiries, contributing to better customer service.

Below is a visual example of these charts:

Average Response, Resolution, and Closure Times

In conversation mode, important metrics related to response, resolution, and closure times are also monitored. These metrics help ensure efficient service and identify areas that need improvement. Below, we detail this information:

Average Response Time

A bar chart showing the average time each agent takes to respond to customer messages. This metric is crucial to ensure customers receive timely responses, improving customer satisfaction.

Average Resolution Time

A bar chart presenting the average time it takes to completely resolve a conversation. This helps monitor problem-solving efficiency and identify potential bottlenecks in the support process.

Average First Assignment to Closure Time

A bar chart showing the average time from the first assignment of the conversation to an agent until closure. This metric is useful for evaluating the overall efficiency of the support process.

Average Last Assignment to Closure Time

A bar chart detailing the average time from the last assignment of the conversation to closure. This can help identify if there are delays in the process of closing conversations.

Below is a visual example of these charts:

Bot Users Report

This report tracks data about the users interacting with the bot, offering a detailed view of user profiles and behavior.

Steps to Access:

Within your bot, go to Analytics.

Select Bot Users from the left-side menu.

Available Report Types

Bot user count statistics

This section provides a comprehensive view of bot user statistics, with detailed charts on total bot users, new bot users, active bot users, and daily average active bot users.

1.1 Total Bot Users

Line Graph: The graph shows a steady increase in the total number of bot users over the period.

1.2 New Bot Users

Line Graph: The graph shows daily fluctuations in the number of new bot users, with evident peaks on specific dates.

1.3 Active Bot Users

Line Graph: The graph shows the activity of bot users over the period, with a significant peak on a specific date.

1.4 Daily Average of Active Users

Line Graph: The graph indicates the daily average of active users, providing a clear view of daily engagement.

Utility of the Graphs

Growth Evaluation: The graphs help monitor the growth in the number of bot users.
Identification of Activity Peaks: Allows identification of dates with high activity, which can be correlated with specific events.
Daily Engagement: The daily average of active users helps evaluate the continuous engagement of users with the bot.

Below is a visual example of the graphs:

Bot Usage Statistics

This section provides a comprehensive view of bot usage statistics, including the number of messages sent and received, emails sent, and email open rate. Detailed graphs on new bot users categorized by gender, language, time zone, country, platform, and device type are also provided.

2.1 Messages and Emails

Messages Sent
Messages Received
Emails Sent
Email Open Rate

2.2 New Bot Users

The following graphs show the distribution of new bot users across various categories.

Gender
Language
Time Zone
Country
Platform
Device Type

Utility of the Graphs

Messages and Emails Analysis: Allows monitoring the volume of messages and emails generated by the bot and the email open rate, helping to assess the effectiveness of email campaigns.
User Profile: The graphs provide insights into the profile of new users, allowing for better segmentation and personalization of interactions.

Below is a visual example of the graphs:

Closing Notes Report

The Closing Notes Report allows you to review the notes left when interactions with users are closed, helping to better understand the context of conversations.

Steps to Access:

Within your bot, go to Analytics.

Select Closing Notes from the left-side menu.

Available Report Types

Category Count and Bot User Graphs

The following graphs show daily variations in the category count and the number of bot users.

Orange and Gray Lines: Represent the category count in the current and previous periods, respectively.

Bot User Graph

Purple and Gray Lines: Represent the number of bot users in the current and previous periods, respectively.

1.3 Category by Bot Users

The following graphs show the distribution among different closing notes added for the bot users. These data help visualize how closing notes are being categorized over time.

Bar Graph: Represents the number of closing notes added in each category for different bot users over the current and previous periods.
Donut Chart: Provides a percentage view of the distribution of closing note categories added by each bot user, allowing for a quick analysis of the proportion between categories.

Inbound Webhook Report

Inbound Webhooks Report

This report shows the received webhook calls and their responses, essential for monitoring integration with other systems and services.

Steps to Access:

Within your bot, go to Analytics.

2 Select Inbound Webhooks from the left-side menu.

Available Report Types

Analysis of Inbound Webhooks from the Last 7 Days

This section provides a detailed analysis of the inbound webhooks recorded by the bot over the last 7 days, with a comparison to the previous period.

General Metrics

Webhook Count
Bot Users

Webhook Count and Bot User Count Graphs

The following graphs show the daily variations in the count of inbound webhooks and the number of bot users.

Webhook Count Graph

Orange and Gray Lines: Represent the webhook count in the current and previous periods, respectively.

Bot User Graph

Purple and Gray Lines: Represent the number of bot users in the current and previous periods, respectively.

Below is a visual example of the graphs:

Error Log Report

Error Logs Report

The Error Logs Report displays error logs that occurred during the bot’s operation, crucial for identifying and quickly fixing issues.

Steps to Access:

Within your bot, go to Analytics.

Select Error Logs from the left-side menu.

Available Report Types

Facebook Ads Report

This report tracks the performance of ads linked to the Facebook Channel, providing essential data to optimize advertising campaigns.

Steps to Access:

Within your bot, go to Analytics.

Select Facebook Ads from the left-side menu.

Available Report Types

Here is a brief explanation for the graphs in the Facebook Ads reports:

Line Graphs

Clicks:
- The orange line represents clicks in the current period.
- The gray line represents clicks in the previous period.
Bot Users:
- The blue line represents bot users in the current period.
- The gray line represents bot users in the previous period.

Filtering

In the Facebook Ads reports, you can filter the data displayed in the graph by all ads or by a specific ad reference payload, allowing for a more detailed performance analysis.

These descriptions provide a clear understanding of how to interpret the graphs and use the available filters to analyze the relevant data in each report.

Facebook Lead Forms Report

The Facebook Lead Forms Report analyzes the leads generated through forms, helping to evaluate the effectiveness of lead capture campaigns.

Steps to Access:

Within your bot, go to Analytics.

Select Facebook Lead Forms from the left-side menu.

Available Report Types

Here is a brief explanation for the graphs in the Facebook Lead Forms reports:

Line Graphs

Clicks:
- The orange line represents clicks in the current period.
- The gray line represents clicks in the previous period.
Bot Users:
- The blue line represents bot users in the current period.
- The gray line represents bot users in the previous period.

Filtering

In the Facebook Lead Forms reports, you can filter the data displayed in the graph by all ads or by a specific ad reference payload, allowing for a more detailed performance analysis.

These descriptions provide a clear understanding of how to interpret the graphs and use the available filters to analyze the relevant data in each report.

Customer Feedback Report

This report shows user ratings and feedback about the Facebook Channel, providing valuable insights to improve service and user experience.

Steps to Access:

Within your bot, go to Analytics.

Select Customer Feedback from the left-side menu.

Available Report Types

Here is a brief explanation for the graphs in the Customer Feedback reports:

Line Graphs

Customer Feedback:
- The orange line represents feedback received in the current period.
- The gray line represents feedback received in the previous period.
Bot Users:
- The blue line represents bot users in the current period.
- The gray line represents bot users in the previous period.

These descriptions provide a clear understanding of how to interpret the graphs and use the available filters to analyze the relevant data in each report.

WhatsApp Conversations Report

The WhatsApp Conversations Report monitors interactions carried out through WhatsApp, essential for evaluating engagement and communication effectiveness.

Steps to Access:

Within your bot, go to Analytics.

Select WhatsApp Conversations from the left-side menu.

Available Report Types

Here is a brief explanation for the graphs in the WhatsApp Conversations reports:

Conversations Cost:

Line Graph:

The red line represents the cumulative cost of conversations over the selected period.

Conversations by Type:

Bar Graph:

The green bars represent paid conversations.
The light blue bars represent free conversations.

Pie Chart:

The green section shows the percentage of paid conversations.
The light blue section shows the percentage of free conversations.

Conversations by Category:

Bar Graph:

The green bars represent marketing conversations.
The red bars represent authentication conversations.
The blue bars represent service conversations.
The gray bars represent utility conversations.

Pie Chart:

The green section shows the percentage of marketing conversations.
The red section shows the percentage of authentication conversations.
The blue section shows the percentage of service conversations.
The gray section shows the percentage of utility conversations.

Messages by Status:

Bar Graph:

The blue bars represent sent messages.
The red bars represent delivered messages.

These reports help monitor the costs, types, categories, and status of messages within WhatsApp conversations, providing valuable insights for performance analysis.

Custom Event Report

Custom Events Report

This report tracks custom events configured in the bot, allowing analysis of specific interactions and measurement of customized user actions.

Note: For these reports to be available, you must have previously created and configured Custom Events. To learn how to do this, access the documentation for this feature from here.

Steps to Access:

Within your bot, go to Analytics.

2 Select Custom Events from the left-side menu.

Available Report Types

Custom Report

The Custom Reports section allows you to view the custom reports available in your bot.

Note: For these reports to be available, you must have previously created and configured Custom Reports. To learn how to do this, access the documentation for this feature from here.

Steps to Access:

Within your bot, go to Analytics.

2 Select Custom Reports from the left-side menu.

Live chat

Besides being able to create chatbot automation you can also follow up with your subscribers through our live chat inbox. We have one available for every channel.

You can access the live chat in two ways:

Through the main dashboard overview
Each individual chatbot channel

How to access live chat through the main dashboard

When at your main dashboard overview you will have a tab on the top named Live Chat.

The biggest advantage of this overview is that you can see all the channels you have built chatbots on. So going to live chat from this main dashboard is very easy. Just select the chatbot and the live chat will appear.

How to access live chat through a chatbot channel

If you are within any of your channels you can also access the live chat from that channel. Just choose Live Chat and the live chat will open up displaying all of your subscribers inside that chatbot channel.

How to access live chat through a chatbot channel

How to use Live chat

Once you select any of your subscribers you will then get to see the live chat in action. Many options and information are present so let us walk you through them.

Section 1 displays subscribers(bot users) who interacted with the chatbot

Click on Inbox to switch between Inbox and Done. When you finish a conversation, move the users to Done.
Use the Search bar to search a conversation by user name.
Click on a user to view conversation detail and user profile.

Section 2 shows the chat your subscriber has with your chatbot

On the top of it, click the <= icon to hide Section 1, the user list area.
Right next to it is the subscriber’s profile photo and full name.
In the upper-right corner, click on the tick icon to move the subscriber to Done.
And the 3-dots icon offers a Hide message from bot option and Manage Shortcuts option.

Hide message from bot lists messages sent only by the user and agent, helping you get a clearer look at the conversation so that agents don’t need to go through too many messages.

Shortcuts help agents make quicker responses to the user’s query. You can also manage your shortcuts in Tools - Shortcuts.

Hover your mouse on a message sent by the bot, click on the little v icon to resend the message or jump to this step in the flow, in case you want to edit anything.

Section 3 allows agents to reply to your subscribers

Write a reply in the blank area.
Type a slash and keyword to search for a shortcut. Use up and down keys to go through shortcuts, hit the enter key to get the pre-written content.
On the right side, </> icon is used to call a variable, e.g. First Name of the user. You might also want to call it quicker by typing to left curly braces {{ and searching a field name.
On the bottom of it, the most left-hand side icon is used to change persona. The default icon refers to the default persona, the chatbot itself. Add persona via Contents - Personas.
Switch between Reply and Note to change reply mode. When you are in Reply mode, the reply area is in white. The content will be sent to your subscriber directly. When you are in Note mode, the reply area is in yellow. The content will be displayed in the conversation area but in yellow and these notes won’t be sent to your users. They are for internal reference only.
the final 4 icons in the bottom-right corner are for sending emoji faces, media (image, gif, audio, video & file) and subflows. The last icon is to send the message/note. You can hit the enter key instead.

Section 4 displays the profile of the subscriber

Section 5 shows notes, tags, subscribed sequences, OTN topics and all custom user fields

Add or remove tags from this overview directly. Very useful when it comes to getting subscribers into lead funnels and such.
For OTN topics and sequences you can only remove them from the user.
The same goes for the user fields, you can view, adjust the values or delete them entirely.

Sending subflows to users

After you finished a talk with a subscriber you might want to send them to a subflow. This is easily done by pressing the icon. A popup window will then appear where you can select or search for your flow.

Once you select your flow press the blue button named Send Sub Flow and the flow will be sent.

NOTE: Do make sure you have disabled live chat mode before sending the subflow. Otherwise the chatbot will not be able to send the messages inside the flow.

💡 TIP - Whenever agents reply in section 3, you will see the Pause Automation area automatically starts a 30 minutes count down. This means that, the chatbot will stop responding during the time. Agents can add on more time if needed. When time is up, the bot starts to reply again.

Livechat Feature : Conversation Starter Prompt

MessagingMe.app now provides even more flexibility to live-agents. We now give users the ability to choose what starts/restarts a conversation. Previously, whenever the agent marks a conversation “Done”. The conversation is moved to the done folder, however if the bot user reaches out again, the conversation automatically moves to the “Open” folder.

This causes confusion among the live-agents between chats do need human support vs chats that do not. We now let users opt-in on this behaviour of livechat.

Turning On Conversation Starter

Inside your flowbuilder’s side menu, scroll down and click on Settings tab. Click on “Live Chat” tab and scroll down till you see “Live Chat Features”

Behaviour When Option is Enabled

Whenever this option is enabled, every new reply or message by the bot user WILL open up the conversation and if the conversation is moved to the “Done” folder, and the bot user reaches out again, the conversation will automatically moved from Done folder to the Open folder.

Behaviour When Option is Disabled

Whenever this option is enabled, every new reply or message by the bot user WILL NOT open up the conversation and if the conversation is moved to the “Done” folder, and the bot user reaches out again, the conversation will remain inside the Done folder until a live agent moves it or it is moved through bot automation.

Using Bot Automations

You can still use bot automations to move the conversations from Done folder to Open folder. This also lets you build a logic flow or apply certain conditions under only which the conversation will move to Done to Open folder.

Live Chat Update: User Data Segments

Introduction

Introducing a new feature connected with Live Chat Section for the User Data.

Now the Live Chat Agent can see the User Data in a more structured method.

This feature shows lots of Data for each Individual User.

Now the User Data are divided basically into sections of different kinds of data inside.

Overview of the feature inside

Now lets jump into the Dashboard Live Chat section as shown in the below Image.

List of Use Data Sections

On right hand side, you can see the Overview Section, where you can see the User data divided into several Sections:

Profile Data
Custom User Field’s (CUF’s)
Notes Section
Tags
Subscribed Sequences
Notification Topics
Shop Orders

Profile Data of User

Custom User Field’s (CUF’s)

Notes Section

Subscribed Sequences

The user data showing the subscribed Sequences, the user might be in Currently.

Notification Topics

Shop Orders

This Feature allows the Live Chat Agent to be little bit more structured instead of needing to scroll down endlessly when having a lot of tags, CUF’s a user has got.

Now you can switch between these several Sections easily with just a Click under one WIndow.

Live Chat Update: Agent Groups

Introduction

We have updated the Live Chat Agent feature.

The feature name is called as Agent Group.

Where to find this New Feature

Let’s see where you can see this feature:

Workspace Settings -> Agent Groups (this is the additional Section, we have newly added).

Now you can click on “+ group**”** to add a new group of Agents together, combine them as per your requirement to get the best Assignment.Possible.

How to set the New Agent Group

Group Name: “Support**”**
Assign Method: “Random**”**

Random - which will be around Robin method
Least Assigned.- In a Live chat agent, that has not many tickets assigned.

Lets select Random assign method as many users prefer to go for Random.

Online First: “Activate**”** (very Important feature)

Soon as Agent gets assigned, then only we check if the agent is Online.

If you want to go with only Live Assignments, choose this option.

Members Overview: The members you can assign as Live Agent.

Weighting: You can also put in the weighting - If this number is high - it means that the likelihood that this Chat Agent is getting assigned will be much much greater.

In Group: You can determine which Member you want to have inside of this new group created and then set the weighting options.

Once all the above settings are done, you can click on “Create” Button.

Now this group will show in the default overview of Agent Groups.

You can customise by going through the Pencil Icon or create one more new Group.

For example you have a Sales Team, a Support Team, a Developer Team, you can create all these kinds of groups .

This is the new group assignment for Agents.

Now you can segment your agents into separate groups and based on this Group, we will also be able to assign the users accordingly.

What an Online Status Verification means for Agents?

Or we can say, ” How are we going to check the agent is Online?”

This works bit different than the regular live chat platforms.

In Messagingme.app , the way we track a Live Chat Agent is Onine is if they have the Live Chat Section in Open Condition.

This means, If we go towards Live Chat for a user means we are now able to check and verify that this Live Chat Agent (Myself in this case) is currently Online.

Incase you move away from this window, that means we are not able to track whether or not the Live Chat Agent is Online.

We need to make sure, that the Live Chat Agent is Online with the Live Chat Section in Open Condition and in that Tab in the browser.

Two ways to access Live Chat

Main Dashboard > Live Chat (from the top Menu next to Dashboard)

Open the Bot > Live Chat (Select from the left side Menu) This is Live Chat for individual Chatbots.

By this we can check the Agent Online status.

Keep the Chat page open on the Dashboard or inside the Bot, that does not matter, as long as the Agent is Present Online on this Specific Window.

How does the Live Chat work inside a Flow Builder?

Let’s create a sample workflow:

Create a subflow in the name of ”Live Chat Agent Assignment”

Action Block -> Basic Actions ->Assign to Agent or Assign to Agent Grou

Let’s select Agent Group.
You can see some options over here.
1. None
2. Default Group 1 - All users (Random)
3. Default Group 2 - All users (Least Assigned)
4. Default Group 3 - Only Agents (Random)
5. Default Group 4 - Only Agents (Least Assigned)
6. (groups customised)

Difference between Group 1-2 and Group 3-4 are:

Group 1 & 2 assigns to all the Users or members inside of the Workspace.
Group 3 & 4 assigns only to the Agent Role Permision itself.
Incase if you don’t want any of the presets you already have, eg., Support Group set up, where we already integrate all of those settings and also provide with available team members inside here.

Updates in the Condition Block

Now you can check a few extra agent settings:

List of Conditions connected to Agent:

Last agent interaction (minutes ago)
Is assigned to agent
Is assigned agent Online
Has agents Online

Let’s go use “is assigned agent Online” in the condition block.

Incase if the agent is not Online or is not in Live Chat, then we are able to go with this Condition block and assign a different agent.

Also we check if the chatbot has any agents available online. If no, we could say “okay, currently we don’t have live chat support, but we will get back to you in particular Business Hours.

We also have a System field called “Last Agent Interaction”, by which you can check the Last Agent Interaction between a certain time frame.

After
Before
Date on
Date between
Time between
Time after
Time before
We have a whole bunch of conditions sets.

With these updates, we have brought some really powerful and amazing features regarding the assignment of Live Chat Agents as well as checking their Online Status, and also the last interaction time of that specific Agent.

By this you are able to provide much better Customer Support Experience for your users.

Merge Bot Users

Merge Bot User

The Merge Bot User feature allows you to merge two user profiles into one, consolidating chat histories, attributes, and other relevant data. This is useful for combining duplicate users and ensuring that all information is unified under a single profile.

How to Use the Merge Bot User Feature

Steps to Merge Users:

Open the Bot User Profile
- In the Live Chat interface, locate the user you want to merge by selecting their profile from the list of conversations in live chat.
- Click on the user’s name to open their profile.
Access the Merge Option
- In the user profile panel, find the three-dot menu (⋮) in the top-right corner.
- Click on Merge Bot User from the dropdown menu.

Select the Secondary User
- In the Merge Bot User dialog box, you’ll see the selected profile automatically designated as the Primary User on the left.
- Use the Choose User dropdown under Secondary User to select the user you want to merge with the primary one. This secondary user’s data will be combined into the primary profile.

Review Details Before Merging
- Before confirming the merge, you can choose whether to delete or keep the Secondary User profile after merge.
- Ensure all details are correct, as the merging process is irreversible.
- The dialog box will display both users’ data for comparison, allowing you to verify which profiles are being merged.
Complete the Merge
- Once reviewed, click in the Merge button at the bottom right of the dialog box.
- A confirmation light box will appear with the message: “All relevant data from the Secondary User will be transferred to the Primary User.” You can then choose to Cancel or Confirm the merge.

Automating the Merge using Bot User API Action Node

You can set up an automated flow to merge duplicate bot users using the Bot User API action node in your flow. This allows you to automatically identify and merge duplicate users based on specific conditions, such as matching email addresses or phone numbers.

Steps to Set Up the Automation:

Create a New Flow
- In the UChat platform, create a new flow or open an existing one where you want to implement the merge action.
Add the Bot User API Action Node
- Before of the Condition node, add an Action node and select Bot User API as the action type to search bot users duplicated.

Add a Condition Node

- Insert a **Condition** node to check for duplicate users. This can involve comparing values such as email or phone number between the current user and other users in the system.

Add the Bot User API Action Node

- After the Condition node, add an **Action** node and select **Bot User API** as the action type.
- Set the **Action** to "Merge Bot User."

Configure the Merge Bot User Settings

- In the Bot User API action node settings:
    - Provide the **Secondary Bot User Ns** (the duplicate user profile to be merged).
    - Choose whether to **Delete after merged** to automatically delete the secondary user after merging.

Publish the Flow

- Once configured, publish the flow. You can set up this flow in a trigger by your choice to enable automatic merging of duplicate bot users whenever the specified conditions are met, ensuring a streamlined and unified user database.

Important Notes:

Merging is Irreversible: Once merged, you cannot undo this action. Ensure that both profiles are verified duplicates before proceeding.

Scheduled Messages in Live Chat

This feature enhances efficiency by enabling agents to plan follow-up messages or send time-sensitive communications without needing to be live. To use, simply type your message, click the schedule icon, select the desired time, and you’re all set.

How to Use Scheduled Messages

In the live chat interface, type your message, then click the schedule icon to pick the desired time for it to be sent. Choose from preset times, like 5 minutes, 10 minutes, 1 hour, or up to 24 hours later. A custom time option is also available, offering complete flexibility.

Types of Scheduled Messages

Scheduled Reply Message

You can schedule a reply message directly within the chat. Adjust the time to fit your needs, and view a list of all your scheduled messages for easy management.
Scheduled Whatsapp Template Message

Schedule WhatsApp template messages effortlessly by selecting the specific template and preferred send time, ensuring seamless communication for WhatsApp users.

Setting a Custom Time

For custom timing, the custom time option lets you schedule messages based on your workspace’s time zone. This ensures messages reach recipients at exactly the right moment.

💡 Note for WhatsApp Channel:
When selecting a custom time that exceeds 24 hours, it’s required to use a WhatsApp template message. Regular messages are only supported for time frames within 24 hours, so for any scheduled message beyond that limit, please choose an approved WhatsApp template to ensure successful delivery.

Managing Scheduled Messages in Live Chat

You can manage scheduled messages in live chat if needed. Although content changes aren’t allowed, you have options to send the message immediately or cancel the scheduled delivery.

Accessing and Managing All Scheduled Messages

To view or manage all scheduled messages, navigate to Tools -> Scheduled Messages. Here, you’ll find an organised list displaying:

Scheduled time
Message type
Message content or template
Bot user
Created by

For each scheduled message, you can either send it now or delete it.

Sortable Options for Live Chat

We have enhanced the Live Chat experience by introducing new sorting options to help agents organize and prioritize conversations more efficiently. Agents can now sort chat conversations based on different criteria, making it easier to track and manage ongoing interactions.

Sorting Options Available

Agents can sort conversations in the following ways:

Last Message
- Ascending (Oldest to Newest)
- Descending (Newest to Oldest)
Created At
- Ascending (Oldest to Newest)
- Descending (Newest to Oldest)
Last Interaction
- Ascending (Oldest to Newest)
- Descending (Newest to Oldest)
Subscribed At
- Ascending (Oldest to Newest)
- Descending (Newest to Oldest)

💡 Last Interaction is based on the last User Interaction. Last message is the last message send from agent or from bot automation.

How to Use Sortable Options

Accessing Sorting Options

In the Live Chat inbox, navigate to the top of the subscriber list. You’ll see the sorting menu that lets you select your preferred sorting criteria.

Choosing a Sorting Order

Click on any of the sorting criteria to toggle between ascending and descending order. The selected sorting option will reorganize the conversation list immediately.
Benefits of Sorting

Sorting conversations by specific criteria allows agents to quickly identify recent interactions, prioritize new subscribers, or focus on conversations that require immediate follow-up.

This update enhances the usability of the Live Chat interface by providing flexibility in conversation management, ensuring that agents can work more efficiently based on their preferences and the needs of their workflow.

Colaborators

We introduce Collaborators, a feature designed to enhance teamwork, improve response time, and provide more efficient customer support.

Why Use the Collaborator Feature?

This game-changing feature allows you to:

Up to 5 users can now work on the same conversation simultaneously
Boost teamwork by enabling multiple agents to collaborate.
Improve response time for customer queries.
Provide efficient customer support, especially when team input is necessary to resolve issues.

How to Enable the Collaborator Feature

Navigate to Workspace Settings.
Scroll down to find the Collaborator Settings and toggle it ON.

How to Use the Collaborator Feature

Open any chat or conversation.
On the right sidebar, just above the user profile, click the “Add Collaborators” button.
Add the agents who need to collaborate on the conversation.

New Filters for Collaborative Conversations

Previously, Messagingme.app offered filters like “All Conversations” and “Assigned to Me” Now, there’s a new filter specifically for collaborative conversations: “Collaborating”

Select this filter to view conversations where you’re a collaborator but not necessarily the primary owner.
This helps team members quickly identify and manage shared conversations.

Collaborator Management Actions

Navigate to Basic Actions to:

Add a Collaborator
Remove a Collaborator
Remove All Collaborators

Chat Assistant Integration in Live Chat

The Chat Assistant is an AI-powered integration within the Live Chat feature of UChat. It helps users quickly generate intelligent responses for ongoing conversations, improving efficiency and support quality. Follow the steps below to set up and use the Chat Assistant.

Step 1: Open the Live Chat Window

Navigate to the Live Chat section of your UChat platform.
Select a conversation from the list on the left-hand side.

Step 2: Access the Chat Assistant

In the chat interface, locate the Assistant button below the message input box (marked with a robot icon).
Click on the Assistant button to open the Chat Assistant panel.

Step 3: Use Custom Prompts

A. Enter a Custom Prompt

In the Chat Assistant window, you’ll find an editable field for the prompt.
Enter detailed instructions or context for the AI to generate the response. Examples:
- “Write a polite message apologizing for the delay in resolving the user’s issue.”
- “Explain the refund policy in simple terms.”

B. Select a Predefined Prompt

If you have set up predefined prompts, you can select one directly from the corner button labeled Select.

For example, you might create options like:
- Apology for Delayed Response
- Order Status Update
- Refund Policy Explanation
After selecting a title, the corresponding prompt will automatically populate the text field “System Message”.

Step 4: Create New Predefined Prompts (Optional)

To further streamline your workflow, you can create custom predefined prompts directly in the Chat Assistant:

In the Chat Assistant window, click the “+ New” button.

2 Enter the following:

Title: A short and clear name for the prompt (e.g., “Delivery Delay Apology”).
Prompt Content: A detailed instruction for the AI (e.g., “Apologize for the delivery delay and assure the customer it will arrive soon.”).
Click Save to store the predefined prompt for future use.

The new prompt will now appear in the list under “Select” lightbox.

Step 5: Review the AI-Generated Message

The generated message will appear in the text box.
Review the content to ensure it aligns with your intended tone and context.
If needed, make adjustments to the message directly in the input box.
Alternatively, you can click Regenerate to have the AI create a new response.

Once satisfied with the message, click the “Use Suggestion” button.

Step 7: Send the Response

Now you will back to live chat window and you can click the Send button to deliver the response to the user in the chat.

Additional Tips

Customize Prompts for Specific Scenarios:

Use detailed prompts to guide the AI for better results, such as “Explain the solution step-by-step” or “Write a message thanking the user for their patience.”

Stay Consistent with Brand Tone:

While the AI generates the response, always ensure it aligns with your company’s communication style.

By following these steps, you can effectively use the Chat Assistant to enhance your live chat interactions and provide faster, smarter, and more personalized support to your customers.

Bot user

People who opt-in to your chatbot by interacting with it are considered bot users. These become contacts inside of your chatbot channel and during the course of a single or multiple conversations, the chatbot will be able to gather information about them to give you more insights into your audience.

You can go to your bot users by going to the corresponding section in the left-hand menu once you have logged into one of your chatbots.

From here you will see a list with a complete overview of all users that have interacted with and therefore opted into your chatbot.

Filter bot users based on conditions

Once on this overview, you can also quickly segment your users by using the filter option. Once pressed you will be able to use any condition/filter you like.

This gives you the ability to quickly see what tags someone has, or what values a custom user fields are.

An example of a filter could be that you want to know who amongst the bot users has given its email.

Another example could be when a user finishes the initial onboarding flow you tag them as such and you want to be able to see who did this.

User information

Once pressing a certain bot user a popup will appear and it will show all the collected bot user details so far.

You will see the following on the left side:

Name
Gender
Language
Timezone
Local time

Below the profile image, you will have the ability to either delete the user or download the user data. This will help you become GDPR compliant as users might request this from you.

You will also see the specific channel user id and some date and time information like subscribed, last interaction and such.

If we go with the right side of the user information you will see tabs for:

Notes
User tags
Subscribed Sequences
OTN Topics
Custom User fields

Only you press one of the tabs you will be able to view the data collected.

For tags, you will have the most options at your disposal.

You will be able to add tags directly to the user but also remove them as well.

For the topics Subscribed Sequences, OTN Topics you will be able to only remove them from the user.

For Custom User Fields you can either remove or change its value.

Importing or creating new users

For the SMS and voice channels, it is also possible to import or create users manually. In the top right, you will have the buttons to do so.

Creating a new user means adding a single user manually whereas Import means you can do this in bulk by means of a CSV file.

Creating and Using Segments in Your Platform

Creating segments based on filtration criteria allows you to retrieve user data efficiently without repeatedly applying the same conditions. This doc will guide you through the benefits and steps of creating and using segments on your platform.

Why Use Segments?

Efficiency: Save segments based on specific conditions and fetch results faster in the future without reapplying those conditions each time.
Convenience: Once created, segments are available for future use, simplifying data retrieval processes.

Steps to Create a Segment

Define the Condition: Set the filtration criteria to segment users based on attributes like tags, location, etc.

Save the Segment: Name the segment for easy identification and future use.

Access the Segment: After saving, the segment appears under bot users, ready for future use.

Using Segments in Live Chat

You can filter users in live chat based on the created segments, ensuring you focus on specific user groups when interacting in real time.

Applying Segments in Flow Builder

Segments can be applied as conditions in the flow builder, allowing you to tailor the user experience based on predefined user groups.

Customizing the User Interface

Field Visibility: To streamline the interface, show or hide fields related to bot users, such as name, avatar, email, country, etc.

Field Placement: You can adjust the position of fields up or down to organize the user data display according to your preference.

Importing Users

The final result of an import may take time for large user lists. The progress and outcome of the import job will be displayed in the Tools section under export jobs.

Boards

In simple terms, boards are tools like Trello or Simple CRM which can be managed within the UChat Platform.

In other words, to explain, we are managing a group of Users, who are taken through several steps/stages of a Funnel system, they are currently In.

A few use cases of the Board are:

Sales Pipeline
Customer Support
Task Management
Project Management

For Example:

Let’s go through the steps of creating a “Board” for the Sales Pipeline.

In the Sales Pipeline, we would Position the Leads for a Business into the following stages:

New Lead
Contacted
Demo Scheduled
Proposal Sent
Closed Won

Creating a Board

Under the Flow Builder Menu, towards the left-hand side, we can find the feature “Boards” just below the “Bot Users” function, and it’s almost the middle of the page.

Now we Click on the Boards feature. we can see a Button called “Create First Board”

Clicking on this Button, we will be proceeding in creating our First Board.

Popup Window - Add New Board

Under Name: We should provide a name to the Board. Eg: Sales Pipeline

Click on “Add Column” to add the First Column and let’s name it as New Lead

Now let’s add the other 4 Columns required into the Board as mentioned above - the different stages in the Sales Pipeline.

Adding the other 4 Columns to the Board

Contacted
Demo Scheduled
Proposal Sent
Closed Won

After adding the 4 Columns, Click on Save Button.

Once we save the Board, we can see that the new Board has been created and all five Columns are created inside the Board.

On this Board Page, you can also create a New Column by just clicking the top right Button “New Column”

Name the Extra Column and Click the Save Button. Now we see the Extra Column added to the Board.

Here in this Board page, we can move the Columns from left to right or vice versa by dragging the Columns to left or to right and position them in a required Order.

We can also see 3 Dots on the top right of every Column. By clicking on it, we can Delete the Column or rename and save the Column.

Once you Click Confirm Delete, the Column will get deleted.

Below you can see we have deleted the 5th Column - Closed Lost

Using Boards

Now let’s see, how to use this Boards Section.

Visual Flow Builder

We shall show the Visual Flow Builder

💡 In the Flow Builder, when we are Guiding the user through a segmentation process and at last we would be having the action block with the Board Function.

We are just creating the Action Block and adding the Board function to it to test its functionality.

In the Action Block -> go to Advanced Actions -> Move to Board function

Next step -> Click on Edit Action in the Board Function.

You need to select the Topic to position the User at the end of a Process.

Now let’s say, we are getting the user to the platform for the first time, so we are selecting the Topic New Lead.

You can also add a Note to the Action taken out of the 3 Options provided in the drop-down menu:

No Change
Update Note
Clear Note

Now let’s select Update Note under the Note Action. and Info under Note Type

Since we are adding the User as New Lead, let the note be as - {{First Name}} is our new Sales Lead

Now we can save the above Note Details in the Board.

Now let’s preview this Action Block with Board Function on the Pop-up Web Page.

We don’t see any action on the Web Page, as we are testing only the Action Block.

Now we close the testing Web page and open the Board and refresh the Page, you can see the Magic:

Under the New Leads Column in the Board, the Guest user has been added. Also you can see the Note: Guest is our New Sales Lead.

Now, You can have a look inside by clicking on the Guest User and you will be able to directly communicate with this User from within the Messagingme.app Platform.

Now you can also drag them to the several stages manually from left to right and right to left.

We can also do Automation, where each time a user takes a certain action, you can move to the required Board. You can move them through all stages of the Board.

Now we have manually moved the Guest User from New Lead to Demo Scheduled.

For example, when we want to do Automation on this, if a Product demo has been scheduled with the Guest User, using the Calendly integration, we can also call an Action with the Board Function, where the following activity is done:

Topic or Stage - Sales Pipeline / Demo_Scheduled is selected.
Note Action: Update Note
Note Type: Info
Topic: Calendly booking is scheduled for Product demo with {{First Name}}

In this way, the Board parameters can be set when a Calendly Appointment is done.

Live Chat

The other way of Changing the Board Parameters is going to the Live Chat . In Live Chat, select the User and at the right hand side list, at the bottom, you can see the Board Function.

Click on the Pencil Icon to change the Parameters after having a Live Chat with the User.

For example as below:

After the Changes have been done at the Live Chat as above, we can see the changes happened in the Board page as below:

Bot users overview

One last way of accessing the Board feature is through the Bot Users.

Let’s see how we can access the Board feature from Bot Users. Click on the Bot Users and select the User, for whom we need to access the Board feature.

Click on the Boards Pencil Icon, to access the Boards Feature for the Bot User Selected.

Now in the Bot Users, you can do the Segmentation of the Users and move them to the Boards Function.

Let’s see how we can do this.

In the Bot Users Page, Click on the FIlter available on top left hand side. Add a Condition to the Users.

For eg: Users having the Tag as FB_leads has to be Moved to Boards.

Now on the Bot Users Page, we would see the Users with Tag FB_lead

Now select the Bot Users by clicking the Check box to the left of the Bot users.

Next Click on the Bulk Action Button on top right hand side.

List of Actions will be displayed and at the bottom, you can see the function Move to Board.

Now you can move the Selected Bot users to the required Activity in the Board.

Basically we use the Board feature to create any kind of small CRM system inside the UChat itself.

In this way, you don’t have to move or export the context towards a CRM system like Hubspot . You can alone create your own sales pipeline. You can create a new Board for appointment systems.

Limitations of Boards Feature:

In one workspace we can only have one Board. In this Board, we can have a maximum of 20 Columns.

AI Hub

Messagingme.app has introduced its powerful AI Agents feature, making it easier than ever to build AI-enabled chatbots without the complexity of handling chat completions and AI assistants manually.

With AI Agents, users can now create advanced, conversational AI bots that seamlessly integrate with OpenAI (and all other popular GenAI platforms), execute tasks independently, and provide dynamic, human-like interactions—all with minimal effort.

Whether for customer support, lead generation, or workflow automation, Messagingme.app’s AI Agents remove the barriers to AI-powered chatbot development, simplifying the process for businesses and developers alike

Template appointment booking AI agent created during the workshop recording can be found here.

Accessing AI Agents and AI Functions

Inside your bot, click on “AI Hub” from the left toolbar to access AI agents and functions.

Creating AI Agent

Click on “+ AI Agent” to create a new AI Agent.

Name & Description:

In this section you will have to enter the name and description of the AI agent. The description will be a brief text that provides enough context on what will be the function of the AI Agent going to be.

💡 Sample Description: This agent is in charge of scheduling appointments with users. The agent needs first to capture the user details which are first name, last name and email. In the next the agent needs to fetch available timeslots and from there let the user choose among them. Once the date and time have been chosen the agent needs to book the appointment

Settings

In this section you will decide which model (and platform) you want to choose and what will be the various parameters that will be modifying the behaviour of the agent created.

💡 Note: If your usecase requires the AI Agent to employ functions, then its always better to use higher models like gpt-4-turbo-preview as higher models are more stable and accurate when using functions.

UChat currently support OpenAI, Deepseek and Grok AI for creating agents. More model will be added soon. including Google Gemini, and Claude.

In this section you can also modifying the various parameters such as temperature value and no of repetitions to further modify the agent’s behaviour

The “Number of chat messages before auto summarize” feature helps manage long conversations by automatically condensing chat history after a set number of messages.

Once the conversation reaches the specified limit (e.g., 10, 50, or 100 messages), the system creates a concise summary of those interactions and reinserts it into the chat as a single entry.

This process preserves key details while significantly reducing character space usage, allowing for more efficient memory management. By summarizing past exchanges, the AI can retain important context without overwhelming the chat history, ensuring smoother interactions.

Additionally, users can customize the maximum token limit for summaries, with 500 tokens being sufficient for general text-based chats and 1,000 tokens recommended for complex tasks like appointment booking. This feature enhances AI performance, conversation clarity, and long-term engagement efficiency.

At the end you can also select the preferred output either in text or in JSON:

AI Agent Advanced Mode

When Advanced Mode is enabled, the AI agent does not reply to the user directly. Instead, it stores the response in the system field “Last AI Agent Reply”. You must select a workflow to process and handle the response before sending it to the user.

Key Features

Response Formatting: Modify AI replies by breaking down long responses into multiple sections for better readability.
Media Integration: Add relevant media files (images, videos, or attachments) to enhance responses.
Workflow Automation: Process AI-generated content through custom workflows to improve message delivery and presentation.

💡 Note: When Advanced Mode is enabled, the Auto Suggestions feature will be disabled.

Agent Prompt

In this section you will define the persona (or how you want the AI agent to behave) as well as its role (or any impersonation) you want it to adhere to.

💡 Sample Role: The Appointment Booking Agent is responsible for scheduling appointments with users. This agent must capture user details, such as first name, last name, and email, fetch available timeslots, allow the user to select their preferred time, and finalize the appointment booking process. The tone should be professional and friendly, ensuring a smooth and positive user experience throughout the scheduling process.

In the skills section, you will have to define all the features you want your AI Agent to perform, whether it be collecting user info data or taking timeslots for appointment booking, everything needs to be defined here. In the skill section, you will also receive insight over which functions you will need to set for your objectives and goals.

💡 Sample Skill:
## Skills

### Skill 1: User Detail Capture

This skill needs to capture the user details which are: first name, last name and email.

ONLY ask for details which are empty or unkown

Once all the user details are successfully captured are you to proceed to fetch the available timeslots and proceed to the next skill.

### Skill 2: Timeslot Selection

This skill needs to display the available timeslots to the user

You are to display the available timeslots in a nice formatted overview

First display the available dates

Once the date has been chosen then you need to show the available times available for that date

### Skill 3: Appointment Booking

This skill needs to handle actual appointment booking

Once the user has chosen the date and time you are to provide the user with the overview of the appointment details and ask them to confirm

Once the user confirms the appointment details you are to save the chosen date and time in its original format as you received it when fetching the available timeslots

once saved you will need to book the appointment

When the appointment is booked you are to notify the user as such

The Product & Service Information feature lets you input detailed descriptions of your products and services, including specifications, booking options, pricing details, and helpful references.

This ensures users can easily access relevant information without needing to ask repeatedly. By providing structured data, this feature helps streamline interactions, improve customer engagement, and enhance the overall user experience.

In the constraints section, you will have to define the behaviours you DONT want your AI to perform. This can include certain questions you dont want to have AI ask or certain words you dont want the agent to use.

💡 Sample Constraints: The agent must only process requests in a single user session and should not store personal data beyond the session. Ensure that all prompts and responses are clear and user-friendly. Handle errors in data input gracefully, providing clear guidance on how to correct mistakes (e.g., invalid email format). If at any step the user decides to cancel, offer an option to exit the booking process politely. Response times should be quick to maintain user engagement and satisfaction.

For your ease, UChat has provided “Generate Agent Prompt” button, which generates the role, persona, skills, and constraints sections based on your given description.

There are two main scenarios where this feature is especially useful. First, if you lack experience in prompt writing, it helps you quickly structure a detailed and effective prompt without needing advanced skills.

Second, if you prefer not to start from scratch, this tool provides a predefined framework, giving you a solid foundation that you can modify and tailor to fit your specific requirements.

Creating AI Functions

Click on “+ AI Function” to create a new AI Function

In the first section you will have to define the name and description of the function.

💡 Sample Description: This function needs to capture user details which are: first name, last name and email. For email the agent needs to validate proper formatting in case the user is not providing it

In the next section , you will have to define the complete prompt for the function (i.e what you want the function to do or perform)

💡 Sample Prompt:
### Skill: capture_user_details

This skill captures essential user information: first name, last name, and email. It ensures that the email provided is in a valid format.

#### Steps for Execution:

1. Prompt the user to enter their first name.

2. Request the user’s last name.

3. Ask for the user’s email address.

4. Validate the email format using a regex pattern (e.g., ^[\w\.-]+@[\w\.-]+\.\w{2,4}$).

5. If the email is valid, store all details; if not, prompt the user to re-enter a valid email.

#### Constraints:

All inputs (first name, last name, and email) must not be empty.

The email must conform to standard formatting rules.

#### Formatting Rules:

Ensure input is trimmed of leading and trailing whitespaces.

#### Error Handling:

If validation fails, inform the user of the specific error (e.g., “Invalid email format”).

Allow a predefined number of attempts to re-enter the email.

#### Conditions:

Proceed to capture details only if the email is valid.

Ask for each user detail separately

ONLY continue with the function call when ALL parameters are captured

In the next section, you will have to define the values you want to fetch from the function (like first name, last name etc) and describe them, as well as to choose which CUF you want them to be saved.

💡 Note: Make sure you check the “Required” check to make the value a must for the function to collect. You can also check “Memory” feature which will go over the conversation history to check if the value already exists. if it does it will skip asking for it again and move on to the next parameter.

At last, you will have to attach the flow (only workflows allowed) that needs to be triggered when the function is called

You can use this feature to send captured values to another platform through native integrations (like googlesheets) or perform API calls via external requests node. It can also retrieve information from an external source and pass it back to the AI agent, allowing the conversation to continue smoothly.

This makes it easy to automate tasks, update information in real-time, and enhance AI responses with the latest data.

💡 Note: You can now use “Send Message” nodes inside workflows. This is done to let AI Agents send media and other dynamic content as per the information received

Selecting the AI Function

For AI Agents to be able to use AI functions, you will have to select them inside the AI Agents modifications.

Once selected, it will look something like this (with an overview of the function prompt)

💡 Note: When deselecting/selecting a function, its prompt will appear/disappear accordingly from the overlay

Using AI Functions

(You can only use AI Functions in workflows). You can select the AI Function Output node from the AI Agents tab in the action block. This will be the data you will feed back into your AI Agent after a function is called and a workflow is processed.

Using AI Agent

Create an action node and select “AI Action:”

Click on Edit Action to select the AI Agent

Select the primary AI Agent (the agent which will trigger and fulfill first) as well as secondary agents (if needed). You can also select the inactivity timeout for the user, that if user stops replying in between conversation with an AI agent, this timeout will trigger and you can follow-up with the users to interact with bot again.

When you select secondary agents, the primary agent will inherit any functions from those secondary agents. However, the primary AI agent’s persona & Role settings & LLM setting will be inherit to the secondary agent.

This feature is particularly useful when you want to enhance the primary agent with additional capabilities without altering its core functionality. By integrating secondary agents, you can expand the range of tasks the primary agent can handle while maintaining a consistent interaction flow(persona & role setting & LLM settings).

At last, save the information in the CUF of your choice. This step is optional, and is designed for debug service only.

If you don’t save the output to any user custom field, the bot response will still send out automatically.

In order to use this AI Agent, all you have to do is send the flow to the user and AI Agent will start conversing with the user.

You can also chain multiple AI Agents(Additional AI agents) together to route the user as per your need. Additional agent will be send the title and short description in the system prompt. Once the intent is identified with additional agent, and then you can connect this intent with another AI agent action.

This will make sure your bot can cover maximum user case, while maintain a optimize usage of your prompt token.

The complete conversation with the user will be saved in the new System JSON field called AI Messages:

AI Agent Incomplete Timeout

Input Incomplete Timeout allows the AI agent to wait for a set period of seconds to capture all responses from the user and process them as a single response. This ensures that the AI agent processes complete user input before generating a reply.

Note: Every new input restarts the timer. For example, if the timeout is set to 10 seconds and the user types “hi,” the countdown begins. If they send another message, like “how are you,” after 6 seconds, the timer resets back to 10 seconds instead of continuing from 7.

Creating AI Tasks

From the AI Hub, click on AI Tasks and then press “+AI Task”.

In the first section, you will have to define the name and the prompt for what you want the AI task to do. AI Tasks are essentially small a combination of chat completions packaged into a bundle which are designed to perform single tasks.

You can use one of the presets available to get an idea of how to fill in the prompt.

In the settings section you can define the settings for model as well as other parameters such as temperature and max tokens

In the output field section, if your AI Tasks requires an output (i.e you are extracting a certain information from a larger text) then you can set a output field where the result will be saved into a CUF.

An example output will look similar to this:

Using AI Tasks

In the action block, click on AI Actions and then select AI Tasks from the dropdown.

Select the AI Task you want to perform and then in the input field, enter the content on which you want to perform the AI Task on,

The end result will look like this:

This value can then be mapped to a user-field to further use it in other flows.

Troubleshooting AI

There are mainly two ways you can go about for troubleshooting the AI responses. The first way way is to analyze the “AI Messages” System JSON field.

You can go to the bot user overview and click on the AI Message JSON to analyze at which step what the user is asking and what responses are being generated by AI.

You can also study when a function is being called:

The second method is to directly analyze the whole conversation from Livechat (with system messages enabled)

Here you can see which AI Agent is being utilized in the flow:

You can also see when a function is being called

Hovering over this reveals the arguments and outputs processed by this function

Similarly you can also see when user fields are being filled.

AI Prompts

Introducing our new AI Prompts feature, designed to enhance the efficiency of your live chat agents.

What Are AI Prompts?

AI Prompts are shared across all bots within a workspace, allowing live chat agents to access predefined AI-powered responses and actions. These prompts help agents save time and enhance response quality without switching tabs or manually translating text.

Where To Find

You can find this feature under AI & Automation > AI Prompts in your workspace.

Select AI Provider

Click the gear icon to access the settings. Select your preferred AI provider and the relevant model:

OpenAI
Deep Seek
X AI
Gemini
Claude

Creating New Prompts

To create a new prompt click the ”+ AI Prompt” button. Provide a name for your prompt and enter the prompt content then set the active status and adjust the display order as needed

We’ve included several pre-built samples for common scenarios:

Tone adjustment (Friendly, Formal, Funny)
Language translation (English, Chinese)
Other customizable use cases

Using AI Prompts in Live Chat

Type your message in the chat window, hover over the AI prompt icon, select your desired prompt then wait a few seconds for the AI to process and you will receive the transformed text.

Example: Translating “Hi, how can I help you today?” to Chinese can be done with just a few clicks, eliminating the need to switch between tabs or use external translation tools.

Auto Suggestions

The AI agent on the webchat channel now has the ability to suggest follow-up questions based on user interactions.

There are two settings available:

Auto suggestion
- Generates follow-up questions solely based on the user’s query.
- May not always include all relevant AI agent knowledge, as it focuses only on the user’s input.
Include Agent Skills & Service Information
- Enhances follow-up suggestions by incorporating the agent’s predefined skills and business-related data.
- Ensures that suggested questions align with the AI agent’s expertise and available business information.
Introduction to MCP Servers

MCP stands for Model Context Protocol, a new feature in the AI Hub that simplifies connecting AI to external tools—no need for complex API endpoint setups.

Key Benefits
- Simplifies integrations with platforms like Shopify, Stripe, Intercom, HubSpot, and more.
- Works with natural language queries.
- Enables access to external tools directly inside your model prompts.
- Cuts down setup time from hours to minutes.
Where To Find

On the left-hand menu, click on the AI Hub, and there you will see the MCP Servers

How to Integrate with MCP Server
- You can connect any custom MCP server, even self-hosted.
- You can connect with OpenAI, Anthropic, etc
- Follow the same process: Name > URL > Optional Auth >Select Tools > Save > Use in flows.
Example: Connecting Shopify

Step -1
- Navigate to OpenAI Playground → Tools → Add MCP Server.
From here, you can integrate various tools like Shopify, Stripe, Intercom, HubSpot, and more, then copy the generated URL for use in your integration

OpenAI Dashboard

Enter your store URL to generate the MCP server URL, view any required authentication, and see the list of available tools.

Step -2

Add A Server

To add a server, simply enter the name, URL, and any required authentication details.

How to use inside Flow Builder
- Go to Flow Builder. → Add an Action block. → Under Integrations, select OpenAI.
- Choose “Create Model Response” → Update model to: GPT-4.1-Mini
- (Recommended due to better compatibility with MCP tools. Avoid GPT-4o-mini/4o)
- Select MCP Servers, set tokens, and temperature
Sample Data

In the sample response, you’ll receive a data list. Identify and select the correct path, highlighted in the example, as it leads to the desired results. Extract the data from that path and store it in a variable.

Beginner and advanced users can both benefit. Users can also host their own MCP servers for custom integrations.

Use cases are endless: CRM, billing, search, data lookup, and beyond.

AI Agents with Web-Search, MCP Servers, and Knowledge Base

Overview

AI Agents introduces major improvements that make it easier to build more powerful and reliable agents. With native support for AI Knowledge Base, MCP servers, and Web Search, you no longer need complicated workarounds or manual functions.

1. Setting Up the AI Knowledge Base

Enable OpenAI Provider

Make sure the OpenAI provider is connected in your workspace. This is required to create and connect vector stores and files. Go to Integrations > OpenAI
1. Preparing Files for Vector Stores
  
  Files must have valid extensions: .pdf, .xls, .doc, etc. Without proper extensions, the system cannot read or index them. Invalid files will cause errors or be rejected. You can upload the Files from your computer or enter the file URL.
1. Creating a Vector Store
  
  Go to the Vector Store section. Create a Vector store and assign a name and set an expiry date (optional, for temporary stores, 0 for no expiry date).
  
  Select the files you have already uploaded in the File section.
1. Building the Knowledge Base
  
  After creating a vector store, create a Knowledge Base. Enter the name, description (optional), and select the associated Vector Stores. Once this is created, you can access it for the AI Agents
2. Setting Up OpenAI Responses Model Inside an AI Agent
1. Setting It Up
  
  Inside an AI Agent, go to Settings → Models. Select OpenAI - Responses. Choose the desired model. Default is gpt-4.1
1. Using Tools with OpenAI Responses
You can now directly connect to the MCP Servers & Knowledge Base to the AI Agent. There is no need to trigger separate AI functions or actions related to them. This will reduce errors and complexity.
1. Web Search Integration
Enabling Web Search allows you to search from the website directly inside the AI Agent. It’s useful if you don’t have MCP servers or a knowledge base. AI agents can fetch answers directly from the web.
- Restricting Domains
  - Format: domain.com, sub.domain.com (comma separated).
  - Exclude https:// or http://.
  - Example: google.com, app.google.com
Limitations by Model For Web Search
- GPT-4.1-mini and GPT-4.1-nano: Web search is supported, but domain restriction is not supported.
- GPT-4.1 (default model): Web search with domain restriction supported.
Notes on GPT-5 Usage (Not Recommended)
1. GPT-5 performs deep reasoning, leading to slower response times and increased timeout errors.
2. Requires more tokens due to extended reasoning. Recommended minimum 2,000 tokens per reply. Note: Higher token usage = higher cost.
3. Use GPT-5 only for advanced reasoning tasks. Keep simpler tasks on lighter models for efficiency
AI Hub - Knowledge Base

A Knowledge Base in UChat is a centralized repository of information that enables AI agents and automation flows to access your business-specific data to provide more accurate and contextualized responses to users.

Knowledge Base Structure

A Knowledge Base consists of two main components:
1. Vector Store: The main container that groups and organizes multiple related files
2. Files: Individual documents containing your business information (PDFs, text documents, etc.)
Important: Knowledge Bases are shared among all bots in the workspace, enabling efficient information reuse.

How to Create a Knowledge Base

Prerequisites
- Connect your OpenAI API Key at:
Workspace → Integrations → Artificial Intelligence → OpenAI

Step-by-Step Guide
1. Access AI Hub
  - Enter any chatbot
  - Navigate to AI Hub → Knowledge Base
1. Create a Vector Store
  - Click “Create New Vector Store”
1. Setting Up the Vector Store
- Define a name (e.g., “Business Info”)
- Set expiration (optional - 0 = no expiration)
- Upload files directly or select existing files
1. Add Files
  - Click “Files” to add more files
1. Create the Knowledge Base
  - Click the ”+” button
- Name your Knowledge Base
- Add description (optional)
- Select the created Vector Store
- Save settings
Where to Use Knowledge Base

1. AI Agents

Location: AI Hub → AI Agents

→ Model Responses → OpenAI Responses

Configuration:
- Enable “Knowledge Base” option
- Select desired Knowledge Base from dropdown
- AI Agent will automatically query these files to answer user question
How it Works: Whenever the AI Agent needs references to create responses about your business, it will automatically access the files in the selected Knowledge Base.

2. Flow Builder

Location: Flow Builder → Actions → Integrations → OpenAI

→ Search Knowledge Base

Available Settings:
- Model Response: Select the response model
- System Message: Configure AI prompt (how AI should respond based on business information)
- User Input: Usually uses the last user text input
- Knowledge Base: Select the knowledge base
- Max Number of Results: Number of results returned (default: 2)
- Max Tokens: Minimum 1,000 tokens recommended for complete responses
- Remove Key Values: Option to remove specific parameters from payload (useful to stay within 20,000 character limit for JSON fields)
Advantages of Creating a Knowledge Base

1. Accurate and Consistent Responses
- AI provides exact information about your business, products, and services
- Eliminates generic or inaccurate responses
- Maintains consistency in shared information
2. Centralized Management
- Update information in one place
- Changes automatically reflect across all workspace bots
- Simplifies maintenance and version control
3. Time Savings
- Eliminates need to train each bot individually
- Efficient content reuse across multiple bots
- Reduces setup time for new agents
4. Scalability
- Easily add new files as your business grows
- Organize information in different Vector Stores by category
- Support for multiple knowledge bases for different contexts
5. Enhanced User Experience
- More relevant and detailed responses
- Reduction in unanswered questions
- More efficient and personalized support
6. Integration Flexibility
- Use in AI Agents for automatic responses
- Integrate into complex flows in Flow Builder
- Combine with other actions and integrations
Best Practices
1. File Organization
  - Keep related files in the same Vector Store
  - Use descriptive names for easy identification
  - Regularly update information
2. Token Configuration
  - For Knowledge Base searches, use minimum 1,000 tokens
  - Adjust according to response complexity needs
3. Monitoring
  - Check file processing status
  - Use “Sync” to refresh view after changes
  - Test responses after configuration

Automation

Keywords

With “Keyword”, your users can easily jump to sub flows by typing in keywords rather than being lost in menus or buttons.

go “Automation” from the sidebar
click “Keywords”
for “default reply”, see explaination below
click ”+ New Keyword”
choose a condition from “is”, “contains” or “starts with”
put one or more than one keyword, separated by only commas, no space allowed
choose a sub flow to send

Default Reply

“Default Reply” is sent when the bot doesn’t know what to reply. When the active button is off or no sub flow was chosen for “Default Reply”, the main flow will be sent.

💡 TIP - So when you build and test flows, you can reply anything to quickly re-start the conversation.
You can also adjust the frequency to send “Default Reply”. Its default value is set to fire “Every Time”.

Advanced Default Reply

Want to have a smarter bot?
Want to reply a sentence rather than a sub flow?
Want your bot to understand more human languages rather than just keywords?

Try Google Dialogflow Integration! Check how to setup Dialogflow.

Sequences

Use sequences to automatically send follow up / delay messages to customers. You can send multiple messages with different delays.

Create Sequence

Follow steps 1 to 3 and you will see this:

5 steps to create a sequence:

give a sequence name
click “Add Message”
edit the settings (see Message Settings below)
choose the sub flow to send
repeat steps 2-4 to add more messages then click “Save”

Message Settings

This is how does the setting window look like:

1. The countdown to send the message

Messages are sent by order.
For the first message, the countdown begins when users subscribed to the sequence.
For other messages, the countdown begins when the previous message is sent.

2. Send anytime or between a time range

For “send anytime”, the message will be sent immediately at the end of the countdown.
For “send between”, if the countdown ends outside the time range, the message will be kept until the next available time.
Remember to check the timezone issue below.

e.g. You don’t want to bother users at night so you set a message to send between 9 am and 6 pm. If there is a message that should be sent at 8 pm, the system will hold the message until 9 am tomorrow.

This can affect the next message because the countdown of the next message begins when the previous one is sent.

3. Send on which days of the week

Similarly, if you don’t want to bother users at weekend, deselect Saturday and Sunday. See the example in the “send between” above.
Remember to check the timezone issue below.

4. Choose corresponding content type (IMPORTANT)

See “Content Type” introduction below.
If you are not sure about which type you should use, keep it default. Although the message might not be sent due to the 24 hours rule, the system will at least help you avoid being banned by Facebook.

5. Pick a notification type

About Timezone

If a channel has a timezone in the user’s profile like Facebook, when the system check “send between time range” and “send on Monday to Sunday” settings, it’s based on users’ timezone first. If the user doesn’t have a timezone or the channel doesn’t support timezone in user profiles, then it’s based on the timezone of the workspace.

Content Type

Any message sent over 24 hours after a subscriber’s last interaction must have a content type that matches its purpose (in accordance with Facebook Policy- Message Tags

Messages with type “Other” or without a content type will NOT be delivered to subscribers who interacted with you via Messenger more than 24 hours ago.

Note - Sending messages that do not match the assigned content type may result in your page being suspended or banned by Facebook.

Default / Other

Can contain promotions and it will only send to users who interacted with your bot in the last 24 hours.

Confirmed Event Update

Send the user reminders or updates for an event they have registered for (e.g., RSVP’ed, purchased tickets). This tag may be used for upcoming events and events in progress.

Post Purchased Update

Notify the user of an update on a recent purchase such as confirmation of transactions(invoice, receipt) and notifications of shipment status(product in-transit, shipped, delivered, delayed).

Account Update

Notify the user of a non-recurring change to their application or account.

Send Multiple Messages

When you send more than 1 message in your sequence, note that all the messages are sent in order.

In the above screenshot, for example, the “Booked” sub flow will be sent “Immediately” once the user subscribes to this “Appointment Follow Up” sequence. Because the first message begins the count down once the user subscribes.

The next message begins the count down once the previous is sent. Thus, the “Appointment Follow Up” sub flow will be sent 1 day after the “Booked” sub flow is sent.

Send Sub Flow

Make some sub flows to send specifically for your sequences. Please note that each Send Message step has its own “Message Tag”. The tag is set to “Other” by default.

Let’s say, now it is over 24 hours since the user last interacted with your bot. You choose a non-default content type for a message in your sequence. This setting automatically changes the message tag of the first Send Message step in the sub flow you send.

Later, if the user responds, you are then able to send messages normally with the “default” content type. So, usually, you won’t need to change any message tag in your sub flow.

Go “Flow Actions”, and you can find the 2 sequence operations.

There are a couple of examples to use sequence, such as

“Event Follow Up” - send confirm message immediately once user registers and follow-up message as reminder or helper
“Get Feedback” - ask for feedback like 2 hours after the user talked to your bot
“Send Coupon” - send coupons when user put something in the cart but doesn’t make an order for a long time

Triggers

Triggers can help you automate certain processes in the chatbot. For example, when a user has opted-in for email you might want to sync this data with a CRM or Google Sheet.

To get to the trigger section you need to go to the left-hand menu and select Automation then choose Triggers. From here you will be able to create a new trigger by pressing the blue button on the top right named + New trigger.

Once pressed you will get to see the available triggers you can choose from;

How to create a new trigger

Let’s take an example of a trigger when someone pays for order inside your chatbot. Press the blue button + New trigger then select the trigger named as such: Order Paid

From here a new pop-up window will open where you can set up the details of your trigger.

You will be able to enable or disable the trigger, set up a condition if you need the bot user to match a certain filter before the trigger is activated, and you can add a note that will explain more about this trigger.

Great if you are working with a team or creating a template and need to clarify things.

Once done press the bottom right button named Save and you are now halfway done setting up your trigger.

Selecting your Sub Flow

Now that the trigger has been created we will be needing to add an action to it. You can do this by pressing the Choose Sub Flow space to the right of that trigger.

Once done it will open up a pop-up window for you where you can select your desired flow to be connected once this trigger has been activated.

You can also type to find your flow more easily if you prefer. Once you found your flow just select it and it will return you to the Trigger overview.

From here you have a few options when it comes to managing the triggers.

Managing your Triggers

You have two options if you want to manage your triggers:

You can enable or disable them by pressing the slider on the left of the actual trigger
You can edit the trigger settings. Inside of here you also have the option to delete the trigger entirely

Triggers

Here is a list of triggers and how to use it:

New user

This Trigger is used when a new bot user enters the bot. This will not work when a user is created manually.

User Subscribed to Bot

This trigger happens when a Bot_User has subscribed to the bot.

User Unsubscribed from Bot

This trigger happens when a Bot_User has unsubscribed to the bot.

User Opted-in for Email

This trigger happens when a Bot_User has Opted-in for Email either manually or by flow

User Opted-out for Email

This trigger happens when a Bot_User has Opted-out for Email either manually or by flow.

User Opted-in for SMS

This trigger happens when a Bot_User has Opted-in for SMS either manually or by flow

User Opted-out for SMS

This trigger happens when a Bot_User has Opted-out for SMS either manually or by flow

Conversation is Open

This trigger happens when a Bot_User conversation is moved to the Open folder in livechat

Conversation is Pending

This trigger happens when a Bot_user conversation is moved to the Pending folder in livechat

Conversation is Done

This trigger conversation is moved to the Done folder in livechat

Conversation is Invalid

This trigger conversation is moved to the Invalid folder in livechat

Chat assigned to an agent

This triggers when Bot_user is assigned to the Agent either manually or by flow

User field value changed

This triggers when a certain specified userfield value is changed for a bot user

Moved to board

You can find more detail about this trigger here

Error logged

Tag Added

This triggers when Tag added to Bot_user

Tag Removed

This triggers when Tag applied to Bot_user is removed.

Label Added

You can find more detail about this trigger in dedicated section

Label Removed

You can find more detail about this trigger in dedicated section

Subscribed to sequence

This triggers when Bot_user is subscribed to sequence

Unsubscribed from sequence

This triggers a sub-flow, when Bot_user is unsubscribed from sequence.

Date/Time based trigger

This is a checklist that serves as a guide when using date and datetime triggers to avoid confusion.

General Guidelines

For both date and date time triggers, make sure that the date or time assigned is always in future. Past dates and times fails the trigger from starting. This is the default behaviour of the platform.
For Channels where timezone is provided by default (webchat, Facebook, Instagram etc) the timezone of the bot user is used for date time triggers.
For Channels where timezone is NOT provided by default, the timezone of the workspace is used for the date time triggers.
UChat will treat all date and date time userfields in UTC time as default, hence if timezone is not provided, the system assumes its in UTC time and then offsets as per the timezone of the user or the workspace,

Date Trigger

Make sure the format of the date when saved inside the date field is UTC standardized. An example of UTC format for date is “YYYY-MM-DD”. Other formats include:

DD-MM-YYYY

MM-DD-YYYY

DD/MM/YYYY

Localized date formats will always cause issues as they are not recognized by the system and will create offsets not synced with the actual time.

Date Time Trigger

Make sure the format of the date time when saved inside the date time field is UTC format. The defacto standard format for date time is “YYYY-MM-DDThh:mm:ss+Z”

here:

YYYY represents the year

MM represents the month

DD represents the day

T represents the separation between date and time

hh represents the hour

mm represents the minutes

ss represents the seconds

Z represents the timezone (Such as +05:00 or -02:00)

Order Paid

You can find more detail about this trigger in dedicated section

Order Processing

You can find more detail about this trigger in dedicated section

Order Shipped

You can find more detail about this trigger in dedicated section

Order Completed

You can find more detail about this trigger in dedicated section

Order Cancelled

You can find more detail about this trigger in dedicated section

Order Refunded

You can find more detail about this trigger in dedicated section

WhatsApp Welcome Message

You can find more detail about this trigger in dedicated section

WhatsApp Order Received

You can find more detail about this trigger in dedicated section

WhatsApp Product Enquiry

You can find more detail about this trigger in dedicated section

WhatsApp Ad Referral

You can find more detail about this trigger in dedicated section

Facebook Ad Referral

You can find more detail about this trigger in dedicated section

Facebook LeadGen

You can find more detail about this trigger in dedicated section

Stripe Invoice Payment Succeeded

You can find more detail about this trigger in dedicated section

Stripe Invoice Payment Failed

You can find more detail about this trigger in dedicated section

CRM V2 Webhook

You can find more detail about this trigger in dedicated section

Shopify Webhook

You can find more detail about this trigger in dedicated section

Woocommerce Webhook

You can find more detail about this trigger in dedicated section

Guest Chat Ended

This triggers a subflow, when the Guest Bot_user ends his conversation, This is helpful for webchat channel for deleting guest users

Calendly - Booked

In this documentation you will learn how to connect your Calendly account to Messagingme.app and then learn how to use the Calendly canceled trigger.

Step-by-Step Guide to Integrating Calendly with Messagingme.app

Step 1: Navigate to the Integration Section

Go to your Uchat dashboard.
On the left-hand side menu, under the “Integrations” section, click on Calendly.

Step 2: Connect Your Calendly Account

Click the Connect Calendly Account button.
This will open a new window where you’ll be prompted to log into your Calendly account.

Step 3: Log Into Your Calendly Account

Enter your email address and click Continue.
Alternatively, you can log in using your Google or Microsoft account.

Step 4: Verify Connection and Webhook Status

Once connected, you will see your Calendly account listed with your schedule URL and the webhook status.
Important: You need to ensure that you have a paid Calendly account for the webhooks to work correctly.

Step-by-Step Guide to use the Calendly Booked Trigger in Messagingme.app

Step 1: Accessing the Trigger Menu

Navigate to your desired chatbot within UChat. On the left panel, go to Triggers under the Automation section, then click + New Trigger and select Calendly Booked.

Step 2: Set up your trigger:

Define the conditions under which the trigger will activate. For example, you can choose to trigger this event when a specific event type is scheduled.

Step 3: Configure the trigger’s action:

In this section, you can set up actions that will be taken when the event is triggered.
For example, you might want to send a notification to a team member through a subflow or trigger a flow with an automatic response to the user who scheduled.

Use the JSON SELECT function (optional):

Within your workflow, you can use the JSON SELECT function to map variables and data as required.

• Customize the mapping according to the needs of your specific automation.

Calendly - Rescheduled

Step-by-Step Guide to Integrating Calendly with Messgaingme.app

Step 1: Navigate to the Integration Section

Go to your Uchat dashboard.
On the left-hand side menu, under the “Integrations” section, click on Calendly.

Step 2: Connect Your Calendly Account

Click the Connect Calendly Account button.
This will open a new window where you’ll be prompted to log into your Calendly account.

Step 3: Log Into Your Calendly Account

Enter your email address and click Continue.
Alternatively, you can log in using your Google or Microsoft account.

Step 4: Verify Connection and Webhook Status

Once connected, you will see your Calendly account listed with your schedule URL and the webhook status.
Important: You need to ensure that you have a paid Calendly account for the webhooks to work correctly.

Step-by-Step Guide to use the Calendly Reschedule Trigger in Messagingme.app

Step 1: Accessing the Trigger Menu

Navigate to your desired chatbot within UChat. On the left panel, go to Triggers under the Automation section, then click + New Trigger and select Calendly Rescheduled.

Step 2: Set up your trigger:

Define the conditions under which the trigger will activate. For example, you can choose to trigger this event when a specific event type is rescheduled.

Step 3: Configure the trigger’s action:

In this section, you can set up actions that will be taken when the event is triggered.
For example, you might want to send a notification to a team member through a subflow or trigger a flow with an automatic response to the user who rescheduled.

Within your workflow, you can use the JSON SELECT function to map variables and data as required.

• Customize the mapping according to the needs of your specific automation.

Calendly - Cancelled

see section resecheduled

Mentioned in Story

This docs covers how to set up and use Instagram story reply and mention triggers within UChat to automate responses and engage with users effectively.

Key Points

Setting Up Story Reply Trigger:

Navigate to Triggers in your automation settings.

Select Story Replied from the new triggers list.

Map elements such as Story ID, URL, and message.
Use filters to customize responses, e.g., avoid triggering for users already in your membership

Creating Flows for Replies:

Create a flow named, e.g., “Mentioned in Story.”
Set the starting trigger to Story Replied.
Customize responses by thanking the user and offering a chatbot starter package.
Use conditions to send specific responses based on Story ID or message content.

Where to get Story ID

Open your post on the browser and copy the ID from the URL.

Here is an example of Live chat when someone replies on story

Automations with Story Mentions:

Set up a trigger for Mentioned in Story.

Map relevant data like Story ID and URL.
Create automated responses to acknowledge and thank the user for mentioning your page.

Example: This trigger will work when someone mentions you in his story.

Here is the Live Chat Preview:

Customizing Responses:

Utilize automation flexibility to handle different story interactions and mentions.

This doc provides a comprehensive guide on leveraging Instagram story interactions to enhance user engagement through automated responses. Use these triggers and flows to streamline your interactions and reward your audience effectively.

Story Replied

You can find more detail about this trigger in dedicated section

Media Post Shared

Automations with Story Mentions:

Set up a trigger for Mentioned in Story.

Map relevant data like Story ID and URL.
Create automated responses to acknowledge and thank the user for mentioning your page.

Example: This trigger will work when someone mentions you in his story.

Here is the Live Chat Preview:

Customizing Responses:

Utilize automation flexibility to handle different story interactions and mentions.

Error Logged Trigger

The Error Logged Trigger allows you to automate tasks and receive notifications when specific errors occur in the platform.

Configuration

Navigate to Automations > New Trigger.
Select “Error Logged”.

Trigger Conditions

1)Error Message Contains: Specify keywords to capture specific errors.

2)Custom Fields: Save error message to a custom field for future reference.

3)Optional: Filter bot users by conditions.

Rate Limiting

To prevent excessive trigger activations, implement a rate limit within your workflow

Benefits

Minimizes unnecessary notifications and automations.

Maintains platform stability and performance.

Facilitates identification of critical errors.

Notification Options

Admin Notification: Build you flow for alerts administrators when the trigger is activated.

Fallback Automation: Executes a pre-defined workflow in response to the error.

Conclusion

The Error Logged Trigger is a powerful tool for error management. By configuring it with appropriate rate limiting and notification options, you can ensure efficient and effective error handling in your workflows.

💡 The platform does not automatically apply a global rate limit for the Error Logged Trigger. Implementing a rate limit within your workflow is crucial to avoid overloading the system and ensure accurate error identification.

Intents(Functions)

For Intents, you have to create an Intent inside automations.

Workflow Example

A sample workflow is demonstrated.

The initial step involves clearing chat history, crucial for looping through the completion until all parameters are captured.

• A simple system message prompts the user to ensure all parameters are captured before finishing the function call.

Output Handling

Output handling involves checking the chat finish reason. Customization options include setting up intents and mapping parameters. It’s essential to test thoroughly to ensure all parameters are correctly captured. Redirecting users back to the chat completion may be necessary if parameters are missing.

• If the reason is a function call, it indicates all parameters are captured, enabling direct output to the user.

The discussed method isn’t limited to appointment bookings but can be extended to various intents.

Comment Keywords

A very important and great feature inside of Messagingme.app is the ability to let the chatbot comment, like and send a person a pm when that person responds to on a post on your Facebook and or Instagram page.

You can find this if you go to the left-hand menu and press Automation then select the Comment Keyword tab.

From here you will have a blue button in the top right corner name + New Comment Keyword.

How to create a Comment Keyword Automation

Once you have pressed the blue button + New Comment Keyword then a pop-up window will open up. From here you will be able to set up your comment keyword trigger.

If we follow along with the image above we have 6 steps to take.

During step 1 you will be able to select any of your Facebook or Instagram page posts depending on which channel you are in.

With step 2 you are able to type in your keywords and determine the condition on when it needs to be triggered. By default, it is on contains, but you have the following options to choose from:

“If comment: Is Contains Starts with Is anything One of the following keywords”

Do note that if you select Is anything the ability to type in your keywords will be disabled.

On step 3 you will be able to create variations with which the chatbot will be able to reply to users who comment on your Page posts.

Advised is to at least add 5 variations to avoid the algorithm marking the replies as spam.

With step 4 you will be able to add the flow that will be triggered when the chatbot will send the pm to the commenter.

NOTE: make sure that your initial message contains only 1 text message with a button. As this counts as a user opt-in the user first needs to interact with this message before becoming a subscriber to your chatbot.

Inside of step 5 you are able to set up a delay for when the chatbot should reply and send a pm to the user.

This will make it more human-like experience-wise. But it is totally optional.

In the final step, you will be able to match any of the settings to your liking.

Once done press the blue button on the top right or bottom name Save and your comment keyword will now be shown in the main overview

How to using AI to automatically reply your Facebook Ads Comments

Introduction

A New Feature has been introduced, where the user comments on your dark post or ads, you can give a Like as well as reply to these User Comments under the comment keyword trigger.

Create FB Ad Post

Let’s create a Ad Post in Ads Manager.

Creating A Comment Keyword Trigger

Automations -> Comment Keywords -> Create New Comment Keyword

Once we click on New Comment Keyword, we can set up this function to trigger our FB Ad Post User Comments.

Let’s set up the required parameters:

We are selecting the FB Ads Post, for which we need to reply for the Ads Post User Comments and give likes.
Comment is Anything, (need to trigger for types of Comments)
Public - Not used

Status set to Active

Save Comment Payload (the Comment information along with the User ID & other details are stored in this JSON Variable for further data retrieving.
Private Reply in Messenger - (selecting the Subflow, which executes when the Comment Trigger happens.

Following Options are turned Active

Reply to new User
Reply to existing Subscriber
Like the User Comments
Reply to replies to Comments

Integration With Facebook Ads Manager

Integration -> Others -> Facebook Ads

Here you are linking your Ads Account Manager along with your FB account Page

Creating the Comment Trigger Flow

Lets go to the Subflow which we have name as Facebook ads comment trigger

Let me explain the concept in building this SubFlow:

Create a Condition block - to differentiate between the Keyword comment chatgpt and general questions asked about your Business / Services
Once the Comment is chapgpt, we are triggering an Action Block where we are calling the Facebook API for Ads Post Comment Reply Action Function.
In this Action Function, we are retrieving and Mapping the Post or Comment ID from the JSON Variable declared in the Comment Trigger Automation.
Next we are sending a PM Message to the User on their Messenger.Channel.
In case the Comment is not chatgpt, we are diverting to another Action Block with OpenAI Integration, where we are doing an Embedding Match with the User’s Comment to check the comment is related to our Business / services we offer and retrieving the related Openai_embed_text.
Incase the Embed Score is >0.8, we are triggering an Action Block by Integration of OpenAI Create Chat Completion Action.
Here we are creating a new variation of the Mapped output of Openai_embed_text, and sending the OpenAI variation reply to the FB Ad Post User’s Comment.
In case the Embed Score is <0.8, the FB Ad Post comment collected in the JSON Variable to be sent to the Action block with OpenAI - Create Chat Completion with a new System Message to OpenAI to answer or greet accordingly if the message is a greeting message.

Condition Block -> Json Variable - “fb_ads_comment match value with chatgpt”

Action Block -> Facebook API -> Ads Post Comment Reply Action

Message Block -> Sending a PM message on Messenger to the Ad Post User Comment

Action Block -> Integration with OpenAI - Embedding Match

Condition Block -> Check openai_embed_score is greater than or equal to 0.8

Action Block -> Integration with OpenAI - Create Chat Completion function

Note: As the page was big, split into two - up and below images includes one page.

Action Block -> Advanced Actions -> Facebook API

End Result as seen on the FB Ad Post Comments

In conclusion, managing comments for your ad posts with OpenAI and ChatGPT is a simple process. By following these steps, you can automate your comment responses and save time. Make sure to customize your replies and settings to your liking, and you’ll be on your way to managing comments effectively.

Facebook Lead Forms

Overview of Facebook Lead Forms

Facebook lead forms offer a fantastic way to collect user information such as name, phone number, and email, with fields prefilled for user convenience. This simplifies the process, requiring users only to submit the leads, kickstarting your automation.

How to set up lead from trigger

Connect your Facebook pages in the Omni channel

Set up instant form leads automation

Under Automation-> Facebook Lead Forms

SMS, Email & WhatsApp Automation

We’ll explore three key automation channels: WhatsApp, Email, and SMS, each offering unique benefits for engaging with leads.

Trigger WhatsApp Template Message:

Connect Whatsapp to the Omni Channel
Trigger a Template Message to start the conversation
When you are adding a New form select Default channel for creating a new bot user WhatsApp

Now select your subflow to send a WhatsApp template message.

Set up your flow by adding a template message.

Trigger SMS Message

Send SMS action

For SMS select select Default channel for creating a new bot user Webchat

Set up SMS Bot and ensure your default reply is configured.

Trigger Email Automation

Set up Email Integration within the Integrations section. You’ll find multiple options to choose from for the Email Channel.

-For email select Default channel for creating a new bot user Webchat

Make sure the user is opt-in for Email or use the “mark email as opt-in” action

Revision Implementation Steps:

Connect your Facebook pages to the Omni Channel.
Create instant forms and link them to your Facebook pages.
Utilize the Facebook List Form settings to automate processes.
Customize flows to trigger actions based on user interactions.
Connect with various channels such as WhatsApp, SMS, and Email.
Use advanced integrations like Open AI to enhance automation capabilities.

How to get the traffic source for the instant form ads

In this article, you will learn how to get the traffic source(campaign name & ad set name) for the instant form leads.

This is the common problem for advertisers. Because in most cases, you might connect the same instant form to multiple campaigns or adsets.

When you received the leads, you will need to find out which campaign or which adset the leads is coming from.

Sample instant form payload

For example, this is the sample instant form lead payload, you can find the details below

And the lead_gen ID is 1091455272135931, and the ad_id is 6526687589538

We will use the ad_id to get more information for the campaign in the next step.

Get the campaign name & ad set name for the leads

You can go to “Action” → “Advanced Action” → Facebook API → “Get Lead Gen” Action.

And then you place the ad_id in the lead Gen ID, and then write “id,name,campaign{id,name}” in the fields(optional), you can pull the details adset name & campaign name in the response as per screenshot below.

If you want to pull more parameters, you can reference the link below to pull more traffic source information

Graph API Reference v24.0: Ad - Documentation - Meta for Developers

Content

User Fields

User fields can be used to store data you collect from your bot users throughout the conversations you have with them.

It will help you segment the users inside of a flow and allows you to create more customized funnels that will help you convert.

Creating a user field

There are two ways to create a user field. We will explain both steps in this documentation.

Create User field in tab overview

To find the user field overview press Contents from the left-hand menu and then select the User fields tab.

From here you will come to your user fields overview where you can manage all of your user fields you create.

To create a new user field press the blue button in the top right corner named + New User Field.

From here a new pop up window will appear where you will be able to set up your new user field.

Just name your new user field. The next step is to select what kind of user field you like to create. Currently, we have the following available for you:

Text
Number
Boolean
Date
Datetime
JSON

These fields allow you to set up all kinds of options inside your chatbot including saving data from bot users or API calls as an array.

You can also add a description if you like and or want to clarify what the function is. Below the description, you will be able to select whether or not you want to move it into one of the folders you might have created to keep user fields more structured and easy to find.

Once you are done just press the blue button in the bottom right named Save and your user field will be created.

💡 For the date time user custom fields, by default, it’s empty. If you are using the default value in the condition node, it will output the “Now” time. If you are using it in the output text, it will show empty value.

Create user field inside flow builder

Another way to create a user field is by doing so directly inside the flow builder. This has the huge advantage that you can create user fields on the fly and not have to go to the user fields overview tab first.

Just go to any flow and from here you can create user fields anywhere you need to use them.

You will be able to create them inside of:

Question blocks
Action blocks -› set custom variable
External request -› response tab

Let’s take an example of a question block. We are wanting to store the response to the question inside of a new user field.

Just start typing a new user field name. The next step is to press the same name below your typed one to create the user field on the spot.

You will then be asked which type of user field you would like to create. Depending on where you are or what kind of question you get to see different kinds of options.

In this case, since it is a regular question block we get to see;

Text
Number
Boolean

Were you to ask for a date/time type of question you would get to see that type of custom field only.

Managing your user fields

To manage all your user fields you can do so at the main user fields overview tab.

You can create folders to keep your user field overview more structured and let you allow to find your user fields more easily.

And you can manage any user field directly from this tab overview by pressing the pencil icon to the right of any user field.

Bot Fields

Similar to user fields you can also create bot fields. The main difference is with user fields you store data to segment and share with that specific bot user, and bot fields allow you to store data and show them all equally among all bot users.

The value does not change. Think of information such as opening hours, or contact details for the business.

Creating a bot field

You can create a bot field by going to the bot field overview tab.

You can do so by pressing Contents from the left-hand menu and from there press the tab called Bot Fields.

If you want to create a new bot field just press the button in the top right corner named + New Bot Field.

From here a pop-up window will appear where you can create your bot field.

After naming your new bot field you can select the type of field you would like it to have.

Currently, we have the following ones available for you;

Text
Number
Boolean
Date
Datetime
JSON

After selecting the type you can start adding the value to this bot field. If you like a description can also be added same as the folder you want to move it to.

After everything is filled in just press the button in the bottom-right corner named Save to create the bot field.

Managing your bot fields

After you created the bot field you are able to manage it from the main overview.

You can create folders to better keep track of your bot fields. You can also enable or disable the template field option.

Lastly, you are able to edit the bot field itself by pressing the pencil icon to the right of any bot field.

Labels

Labels function similarly to tags, however they can be accessed across different bots in the same workspace.

💡 This is extremely helpful if you have purchased the “Global Contacts” Paid add-on.

How to use Labels

Where can you find it: Under Content, you can see the labels

To explain how labels work, we have two bots in the same workspace. One of them is Whatsapp Bot, while the other is Omni Channel.

When you create a label, you can access it in all bots that share the same workspace.

How you can use in sub-flows:

In action node -> basic action -> add and remove label.

You may now view these labels in Live Chat.

How to use the Labels in the “Global Contacts” Add-on

Purchase Global Contacts Add-on

This is only available to UChat partner plan. You can purchase the add-on at one time cost. You can find the add-on from your “Whitelabel Settings” → Partner Settings → Custom Addon → Global Contacts.

Once the add-on is purchased, you can click “settings”, it will show you where you can find this settings.

It’s located in the “Live Chat” at the top navigation bar, and you can find the “Search Bot Users” from the left side.

How to use workspace labels in Global Contacts

The workspace label is shared across different bots in the same workspace. so if you have added the same label in different bot, it’s possible for you to filter out all the bot user that meet your segment requirement.

In the global contacts, you can click the “filter” icon, and then build and share the segment based on the workspace labels.

For example, we have created “new customer” label, and it’s shared across all the bots in the same workspace, and you can create the filter like the screenshot below

Once it’s saved, you can save this as public or private segment, and then your team can access these contacts easily from the left sidebar.

Nodes

We’ll guide you through the powerful node feature in Messagingme.app. This feature allows you to efficiently manage and interact with the nodes in your workspace, making your workflow smoother and more organised.

Navigating and Filtering Nodes

Selecting Flows

To start, users can select flows within their bot. This selection will dynamically display all the nodes in the chosen flow, giving you a comprehensive view of the workflow.

Filtering Nodes

Users can filter nodes by different types, making it easier to locate specific nodes based on their functionality. Additionally, you can search for nodes by their name, streamlining the process of finding exactly what you need.

Using Node NS

Finding the Node NS

To get the Node NS, follow these steps:

Go to the Flow Builder.
Click on one of the nodes.
Look for a list icon; this will copy the Node NS.

Searching with Node NSs

Once you have the Node NS, you can search for it directly in the node feature. This makes it quick and easy to jump to specific nodes without manually navigating through the entire flow.

Opening Specific Nodes

You also have the option to directly open certain nodes using their Node NS. This feature takes you straight to the node, saving you time and effort.

Managing Node Limits

Node Limitations

UChat has a limit of 2000 nodes per workspace. If you exceed this limit, you may need to purchase additional nodes.

Purchasing Additional Nodes

For every 1000 extra nodes, the cost is $20 per month. If you require more than 2000 nodes, please reach out to UChat support (ticket@uchat.com.au) for assistance.

Performance Considerations

Exceeding the 2000-node limit can impact the performance and speed of your bot. We recommend optimising your nodes and deleting any flows that are no longer in use to free up space and maintain optimal performance.

Custom Events

Messagingme.app now allows its users to track various events that happen within the bot automations and let users visualize these event via analytics in form of custom events and custom reports.

Creating and Using Custom Events In UChat

On your dashboard, click on the bot and go inside the flow builder.

Inside the flow builder, select Content tab, and then select custom events.

When creating a new event, following parameters you have to provide.

Event Name : This is used to naming that custom event

Event Description : This is used for describing what the custom event do and track.

Parameter Names : These are the name of the parameters you want to track for, for example product, sales category, name of the person etc

💡 You dont have to fill each of the parameter in order for the event to work but you need to be able to provide atleast one parameter for tracking

After creating an event, Go inside your flowbuilder and add the “Custom Event” action from Action block to start integrating the event and tracking it.

Click on Edit action and start setting up the event.

Here the event will track the Channel from which the users are coming and then the count will add one count to the total number of event happening.

The event is now ready to be tracked.

Visualizing Analytics For Custom Events

Click on the analytics tab, select custom events to view the analytics for that particular event.

Click on the event to further view the analytics of that particular event.

Closing Notes

Messagingme.app now allows its users to extend the livechat functionalities using Closing Notes. Closing notes allows live agents to provide more context for when a conversation is closed or moved to done.

Creating Closing Notes

Inside the bot, click on “Contents” and then “Closing Notes”.

Click on “+ New Category”

Click on Save to create a new category.

Enabling Closing Notes

Go to the Settings tab and click on Livechat settings. Enable the closing notes.

Once done, click on Save and you will be able to use closing notes.

Using Closing Notes

Closing notes can be used when moving a conversation to “Done”. When moving a user to done, if closing notes are enabled, the live agent will be prompted to enter the closing note.

The closing note can also be observed from the bot user overview.

Closing Note Trigger

Once a closing note has been applied, it can be used as a trigger to run automations.

This trigger is useful for notifications, analytics and other bot user related automations.

Closing Note In Condition Node

You can segregate users based on closing notes in a condition node as well.

Closing Note Analytics

You can access closing note analytics by going to the analytics tab.

User Menus

For Facebook bots, you can have a persistent menu with 3 buttons at most. To setup:

go “Tools” from the left sidebar
click “Persistent Menus”
“Edit Menu”
”+ Add Menu”
give menu title
select a menu type, “Goto sub flow”, “Open website” or “Open checkout page”
choose a sub flow or name a website address

Personas

Personas will help you to make your chatbot come over as more human. It allows you to set up a personal profile with profile pictures so people are more inclined to talk with the chatbot since they feel it is a more personal experience.

Creating and managing your Personas

To create a new persona you can go to Contents from the left-hand menu, then to the Personas tab.

From here you will have the main overview of all the personas you have created inside the chatbot.

If you want to create a new persona you can do so by pressing the top right button named + New Persona.

From there a pop-up window will appear where you can set it all up.

Once created the persona will be available for you inside the main overview.

From here you can also manage your persona inside that main overview. You only have to press the pencil icon to be able to edit.

How to use Personas

You can use personas by setting them inside your flows.

Just go to a flow and create an action block. From here select Advanced actions, then Set persona.

From here you can select any kind of persona you have created previously and the chatbot will then continue the conversation with that user with that profile.

Using personas is a good way to increase engagement and conversions as well. Female personas often do very well with men so you could start your flow by checking with a condition which gender the user is and then set the persona accordingly.

WhatsApp Flows

WhatsApp Flows is a feature currently under development that enables you to create automated chat sequences specifically for WhatsApp interactions. These flows guide users through predefined steps, improve response efficiency, and enhance customer engagement.

Accessing WhatsApp Flows

Navigate to the “Chatbot” section within your UChat workspace.
Select “Content” from the available options.
Under “Content,” locate and click on “WhatsApp Flow.”

Creating a New WhatsApp Flow

Click on “Create Flow” to initiate the creation process.
Provide a name for your flow (e.g., “Lead Signup”).
Choose a category that best describes your flow’s purpose (e.g., “Lead Generation”).
Click “Create” to confirm and proceed.

Customizing Your WhatsApp Flow

Welcome Screen: Edit the text, heading, and content displayed on the initial screen that greets users.
Adding Interactive Elements: Utilize the editor to incorporate interactive elements like text capture fields (name, email, etc.) with desired input types (text, number, etc.) and optional requirements.
Building a Multi-Screen Flow: Construct a flow with multiple screens by adding new screens and guiding users through a sequence of interactions.

Allow to edit the screens for published WhatsApp flow

You can now update the screens of your published WhatsApp flows directly from the dashboard!

With the new “Edit Screens” option, making changes is smoother than ever, there is no need to unpublish or interrupt your live workflows.

This feature helps you stay agile and make real-time improvements effortlessly.

Testing and Previewing Your Flow

Flow Preview: Utilize the eye icon to preview your flow’s appearance and functionality from a user’s perspective.
Testing the Flow: Engage in a test interaction with the flow to ensure it functions as intended.
Publishing the Flow: Click in “Publish” and “Confirm”

Connecting the WhatsApp Flow to Your SubFlow

Within the Flow Builder, select “Text Note” under the “Omni Channel” section.
Choose “WhatsApp Cloud” followed by “WhatsApp Flows” from the available options.
Edit the message content displayed after the WhatsApp flow is completed (e.g., “Sign up today”).
Select the desired call to action text (e.g., “Claim Access Now”).
Associate your created WhatsApp flow (“Lead Signup” in this example) with this step.
(Optional) Configure payload saving to a JSON field named “data” to capture user information collected during the flow.

You can now populate sign-up forms with custom user fields directly within the flow builder. This allows for a more dynamic and personalized user experience. Follow these steps:

Add a WhatsApp Flow using a Message Node:
- Within the Flow Builder, select “Send Message” -> “Others” -> “WhatsApp Flow”:

• Click “Edit” to open WhatsApp Flow settings

• On the editing pop up, enter the data such as Body, Button Text and select your WhatsApp Flow:

In the “Inputs” section, you will see an option to map the inputs to existing custom user fields in your Messagingme.app account.
For example:
- Field: Name → Map to Custom Field: {{user_name}}.
- Field: Email → Map to Custom Field: {{user_email}}.*

(Optional) Configure payload saving to a JSON field to capture user information collected during the flow.
1. Save and Test:
  - Save and test to ensure that the data entered into the user fields matches the bot user data.
Conclusion

WhatsApp Flows provides a powerful tool for designing and testing automated WhatsApp chat experiences. By following this guide and experimenting with the features, you can gain valuable insights into how to leverage this functionality to enhance your customer interactions.

Notification Topics

For meta channels (Facebook, Instagram, Whatsapp), users have a limit that they can only be contacted within 24 hours of the interaction. Afterwards you are unable to send them any more messages of automations

For this use case, Facebook has introduced notifications to be sent to users after subscribing them to it. These help you continue your automations past the 24 hour interaction limitation.

You can read more about them here:

Marketing Messages - Messenger Platform - Documentation - Meta for Developers

How to Create Notification Topics Inside Messagingme.app

Inside your bot, click on “Content” then “Notification Topic”

Click on “New Topic” to create a new notification topic

Types of Notification Topics

There are two types of notification topics that Facebook allows us to send to the users.
1. One Time Notifications (OTN) - Can only be sent once
2. Recurring Notifications - Can be sent on a recurring interval of time
Both of these notification types require the user’s consent and they will have to explicitly subscribe to these notifications before we can send it to them.

One Time Notifications (OTN)

To create an OTN, click on the “New Topic” then select “ONCE” from the type.

Once done, click on Save.

Before we can send this to a user, we first need to subscribe them to it. For subscription,

Create a “Send Message” node, then click on Notification Message. Then select “OTN Request” option.

Select the topic you want to send, add some test and then send it to the user. Once they click on “Notify Me”, you can then subscribe them to a sequence to then send them the OTN whenever the need arise.

Recurring Notifications

Click on “New Topic” and select “RECURRING” option from the frequency tab.

To subscribe the users to a recurring notification, create a Send Message node, then select on Notifications and then select “Daily Notification Topic”

Similarly if they click on “Get Messages” you can subscribe to a sequence that will send them the recurring messages on the interval of your choice.

How to Send Notification Messages

To send notifications (both OTN and recurring) , create a Send Message node, select Notifications and select “Send Notification Message”

Select the topic that you want to send, then once done, the message following the message above should contain the notification message. For example:

The last send message node in this flow is the content you want to send to the users while the middle node is the initiator to let Facebook know that this is a notification.

Customer Feedback (Facebook)

A fantastic way inside the chatbot to collect feedback is to use Messgaingme.app native module for this. It will allow you to gather not only feedback but also allows you to know when a user is not satisfied with the product or service you provide, which you can then proactively contact to resolve any issues there might be.

Note: This is only available inside the Messenger channel.

Creating and managing Customer Feedback Topics

To create a new customer feedback topic you can go to Contents, then select the Customer Feedback Topics tab.

From here you will see an overview of all your created topics and it allows you to manage them or create a new one.

If you like to create a new topic you only have to press the top right button named + New Feedback Topic.

Once done a pop-up window will appear where you can set everything up.

As you can see you can fully customize this to your own liking so let’s walk through the options.

With option 1 you can give the topic a name as it will appear inside the topic overview. Below that you will be able to adjust your Question title. This will show up as the question. By default, there is a question inside but you can adjust it if you like.

You can also set the type. You have the following choices;
- Customer satisfaction score
- Net promoter score
- Customer effort score
- Free input form
The next step is to select your score label. You will have the following options;

Next up are the score options that you will be able to choose from;
- One to five (numbers)
- Five stars
- Five emojis
You will also be able to enable or disable free form input. Once enabled the user will be able to give additional feedback outside the rating.

Below that you will be able to point to your privacy policy which is mandatory. And lastly, you will be able to set the customer feedback to expire anywhere between 1-7 days.

Once done you can press save. You will be taken back to the main overview and you will be able to manage the customer feedback topic you just created from there.

On the right you will have two icons. The first one will show you advanced analytics on the topic you selected, while the pencil icon allows you to edit it to your liking.

Below you will find an example of the analytics you can expect;

How to send a customer feedback topic

This is easily done inside of the flow builder. Just go to any flow you want to set up for this. From here create a send message block, then select Customer Feedback.

You will then be able to add a title and subtitle and press the button named rate experience.

You will then be able to give the button a title, select the topic you want to use and save the responses to a user field. Once done press save you will be able to send this customer feedback to any user that enters the flow and this block.

This link will redirect you to the WhatsApp template section in WhatsApp manager, and you can create & submit template directly in WhatsApp manager, and once the template is approved, you can go to Messagingme.app to sync the template back to Messagingme.app.

Tools

Error Logs

Error logs can help you troubleshoot bugs that can happen inside your chatbot. It can save you a lot of time trying to figure this out yourself otherwise.

To access the error log you can go to Tools from the left-hand menu, then select the first tab called Error logs.

From here you will have a complete overview of all errors that have happened in the chatbot.

From here you can see the date of the error, the kind of error, which user it affected, which sub flow it happened in along with the node that has the error, and more information.

If you press on the node of the error message it will take you directly to the point where the issue was registered at.

This will speed up troubleshooting immensely and save you hours you otherwise would waste in trying to find the bug.

Error log trigger

You can find the “Error log trigger” under Automation → Triggers.

You can also narrow down the message content in the errors.

💡 Error log only trigger once in 24 hours for each user.

Testers

To help you with testing your flows before they go live you can invite testers inside your chatbot. This will help you troubleshoot any potential problems that are happening in your flows.

So to clarify a tester can view a flow that is not yet published.

Assume you have a published onboarding flow that is accessible to the public, but you made changes in the backend which are not yet published. You will be able to let testers preview those flows.

To invite a tester they will need to be a subscriber to your chatbot.

Invite and manage testers

To invite a tester to your chatbot just go to Tools from your left-hand menu, then select the Testers tab.

To create a new tester just press the button in the top right corner named + New Tester. From here you will be able to type in the name of the person you would like to be a tester inside your chatbot.

Again do note that this person you want to appoint as a tester needs to be an active subscriber of that chatbot.

Once done you will return to the main overview for the testers where you can also manage them from.

You will see the users who are invited by you as a tester and if you want to delete them you can press the trashbin icon to the right of each user to do so.

How to send testers flows

To send testers the flows in the draft version you can do so in a few ways.

You can share a link to the particular flow, or let them type a keyword that will trigger the flow.

Another way to let testers view content regular users cannot is by using the condition inside the flow builder for it.

Just go to any flow and insert a condition block. From here search for the condition named is tester.

This way you will be able to send a tester to one part of the flow you want to be tested and a regular user can just follow the flow already fully published.

Debug with test users

If the user is a test users, and then every flow the user go through will show up in the tools → error logs. This is the full debug mode.

It is really helpful if you want to figure out the exact flow the user have taken, and help to debug the potential issues.

Don’t forget to remove the test users once the debug is done.

Admins

Besides the regular members, you can invite to your workspace you can also invite admins to your chatbot only.

With a condition you can set up admin menus for them they can access like getting a report or wanting to get some insights into the chatbot.

#Invite and manage admins

To invite an admin go to Tools from the left-hand menu and select the Admins tab on top.

From here you will get to the main overview.

To add a new admin the user you want to invite needs to be a subscriber to your chatbot. If they are then press the button on the top-right corner named + New Admin.

From here a pop-up window will appear where you can search for and add a new admin.

Just type in the name of the person you want to have as an admin and press the plus sign to have them added as an admin. Once you press the plus sign you will return to the main menu where you can manage all admins.

At the right of each admin, you have the option to delete them if you like.

How to set up an admin flow

Now that you have appointed an admin you can set up admin specific flows for them. This is ideal if you want to give a business owner some insights as to what is going on inside the chatbot but don’t want to give access to the backend of that chatbot.

Just go to any flow you like and insert a condition block. From here search for the condition Is Admin.

If the condition is set to yes you can send the admin to the admin mode where you can set up access to whatever you like.

An example could be;

It is a great way for business owners to get access to certain features on the front end while not having to worry about them having access in the backend.

Widgets

For Facebook bots, you can set some widgets to quickly start talking to the bot. To setup:

go “Tools” from the left sidebar
click “Widgets”
”+ New Widget”

put a widget name
choose a sub flow the link goes to

(leave 3 and 4 blank if no reference is needed)

put a parameter name
assign a custom user field

What does the Ref parameter do?

For instance, you make a messenger ref URL to your main flow, so that by visiting this URL, your users can start talking to your bot.

However, you would like to gather more information from the link, like where did your users get the link? In this case, you can put “source” in area 3 and a variable to store the source at area 4 in the above picture.

Later, add a source name in your link according to where do you put it. This is how you get extra information from the link.

After filling in all the information, click “Save” and click the pencil to edit this widget, you will see a unique URL generated for this widget:

So here, by visiting any of the following links, your users can start talking to your bot:

example link	value in variable “source”
https://m.me/102942588321862?ref=source
https://m.me/102942588321862?ref=source—advertisement	advertisement
https://m.me/102942588321862?ref=source—shared_by_users	shared_by_users
https://m.me/102942588321862?ref=source—promoted_by_sales	promoted_by_sales

Yes, you might notice that by adding “—xxx” after the link, the value “xxx” will be transferred to the bot.

URL links are convenient to click via electronic way while QR codes are more suitable for on-site use. By scanning a QR code, your users can start talking to your bot.

To setup:

give a widget name
select a sub flow
upload your logo image
adjust image size if needed
adjust color if needed
adjust dot scale if needed
click “Generate” to get an image on the right. Repeat step 4, 5 and 6 to get a final image
download your QR code, print it and put it in your store, restaurant, office, etc

To setup:

give a widget name
select a sub flow
adjust theme color if needed
adjust greeting message which will be shown above the “Continue as xx” button (see in the previous picture).
select a display type
adjust the delay if the second or the third display type is selected
for payload, see explanation in Messenger Ref URL above.

Click “Save” after finishing all the settings, again, click the pencil to edit this widget and you will see this button:

Click it.

Add the websites that you want to put this bot at. Then install the snippet by copying and pasting the code.

Perfect! 😎 You got a bot on your website now.

Chat Buttons

Here are the steps to add a custom “Powered By” text and URL link to your chat widget on Messgaingme.app . This feature allows you to include a custom signature or link in the footer of the chat widget.

Please note: This feature only applies to the Button Widget and does not work with the WebChat Widget.

Key Differences:

Button Widget: Redirects users to a specific channel of communication when clicked. The “Powered By” text in the Button Widget can be customized starting from the Business Plan. For example:

• WebChat Widget: Functions as a complete chat channel where users can interact directly without redirection. Customization of the “Powered By” text in the WebChat Widget is only available for Partner Plan clients. For example:

Step-by-Step Guide

Access the Widgets Menu
- In the Messagingme.app dashboard, go to the left sidebar and select Widgets.
Create a New Widget
- Click on + New Widget in the top right corner.
- Choose the Chat button option from the dropdown menu.

Name the Widget
- In the Add New Widget screen, enter a name for your widget in the Name field, then click Save.

Edit the Widget
- After creating the widget, locate it in the widget list and click on the Edit icon (pencil icon) next to the widget you want to configure.

Set Up “Powered By”
- In the widget settings editor, you will see customization options.
- Find the fields labeled Powered By and Powered By URL:
  - Powered By: Enter the text you want to display as “Powered By.” This text will appear at the bottom of the chat widget.
  - Powered By URL: Enter the link to which the user will be directed when they click on the “Powered By” text. This link can lead to your website, a contact page, or any URL of your choice.

Save Settings
- After configuring the “Powered By” text and URL, click Save to apply the changes to the chat widget.

These steps will set up the “Powered By” text with a link in your widget, providing a personalized experience for users interacting with the chat on your site.

Multiple Languages

With Messagingme.app you have the ability to provide a multiple language chatbot experience. It is very easy to set up as well.

How to Select the Language

Navigate to the Multi-Language Settings
- Go to Tools in the left-hand menu.
- Select Multiple Languages from the dropdown.
- Click on New Language.

Choose Your Preferred Language

You will see a list of available languages.
Select your preferred language from the list.

Translate Your Flows

Click on Translate.
Select the flow you want to translate.

• Translate each node in the flow into your preferred language.

Setting Up Language Selection in Your Flow

Add a Language Selection Option

Go to your flow in the Flow Builder.
Add an Action node where you want the user to select their language.
In the Action node, select Advance Actions and then Set Language.

Visual Example

Here is how the flow setup will look:

Shortcuts

This document explains the new import feature for Live Chat shortcuts, allowing you to save time by importing them in bulk.

What are Live Chat Shortcuts?

Live Chat shortcuts are pre-defined snippets of text that you can insert into chat conversations quickly and easily. They are ideal for frequently used information or responses, saving you time and effort.

Benefits of Importing Shortcuts

Save Time: Importing shortcuts eliminates the need to create them individually within the UChat platform, especially if you have a large amount of existing content.
Improved Efficiency: Importing shortcuts streamlines your workflow by providing a faster way to populate your shortcut library.
Reduced Errors: Importing from a well-organized CSV file minimizes the risk of typos or inconsistencies that might occur during manual creation.

How to Import Live Chat Shortcuts

Access the Shortcuts Section:

In your bot navigate to the “Tools” section within the UChat platform.
Select “Shortcuts” from the available options.

Locate the Import Feature:

Click on the dropdown arrow in the top right corner.
Choose “Import” from the menu.

Prepare Your CSV File:

Use a spreadsheet tool like Google Sheets to create a CSV file.
The CSV file must have two columns:
- Shortcut Name: This column will contain the names you assign to each shortcut.
- Description: This column will hold the actual text content of each shortcut.

Export the CSV File

Click “Download” to save a copy of the formatted CSV file.

Import and Map CSV Columns to Shortcut Fields

Drag and drop the downloaded CSV file onto the import section in the UChat platform.
Verify that the “Shortcut Name” column is mapped to the “Name” field and the “Description” column is mapped to the “Value” field.

Confirm Import:

Click “Confirm Import” to initiate the import process.

Verify Imported Shortcuts:

The platform will display the number of successfully imported shortcuts.
You can now access these shortcuts within your Live Chat conversations.

Using Live Chat Shortcuts

Access a Live Chat Conversation:

Open any ongoing or new Live Chat conversation.

Insert a Shortcut:

Type a slash “/” symbol within the chat window.
A list of your available shortcuts will appear.
Select the desired shortcut from the list.

Send the Shortcut:

The content of the selected shortcut will be automatically inserted into the chat window.
Press “Enter” to send the message to the customer.

Conclusion

The import feature for Live Chat shortcuts is a valuable tool that enhances efficiency and saves you time when managing frequently used information within your customer interactions. By following these steps and utilizing the import functionality, you can easily populate your shortcut library and streamline your Live Chat communication.

Export Jobs

Messagingme.app now allows its users to export all bot users (or filtered bot users) into a csv file and download it directly.

Previously we sent the CSV file via email but due to SMTP issues for partners and other email-related issues, we changed the feature to now support in-platform download option.

Accessing Export Job

Go into your flow builder and click on the bot user’s tab. Apply a filter on bot users (or if you want all bot users) and click the download icon button at the top right.

A prompt will appear stating to export the selected bot users.

Another prompt will appear, ignore the wording that the exported csv will be sent to your email, instead go into tools section

Clicking on the download button will save the CSV file to your device

💡 If you are importing contacts into the bot users, the import progress & status will also show up in this section.

Custom Reports

Creating and Using Custom Reports In Messagingme.app

In order to create a custom report, click on the tools tab and select custom reporting.

Enter the name of the report and the type of the report.

Click on the gear icon to start modelling your reports.

Modelling Funnel Report

Click on the “Funnel Steps” to start adding custom events to your report

Click on “Add step”

Select which type of event do you want to track

After adding the event, click on the three dots icon to start customizing it.

Set up the proper events you want to track in this event. Click on the Done button

You can add more steps to your funnel report, if you want to build a collaborative report or comparison report on multiple events and track the performance on multiple fronts.

If you want to change the colors of the trendline graphs and bar charts, click on the palette icon on the tope left corner and then choose the chart you want to change the color of.

You can also edit the graphs and charts themselves, changing their labels, axes, enabling or disabling them to show on the report itself or not

Modelling Percentage Report

In percentage reports, you can compare two events and find out how they perform w.r.t to each other.

In order to add the events, click on Field A and Field B.

In order to edit the charts and graphs, click here to modify them as per your needs.

Formulae

Percentage reports allow you to add formulae to calculate the percentage and proper event.

Formula #1

This formula compares the two fields and calculate the relative percentage between them. For example

Field A can be No of students in Class A and Field B can be the total number of students in a school, this formula will help you calculate the percentage of students of Class A compared with total student population of the school
Field A can be can be the no of sales of product A and field B can be the total number of sales, this formula will help you calculate the percentage of sales of product A.

Formula #2

This formula compares the two fields and just like the formula 1 give the relative percentage. Here Field A and Field B can be the two parts. The denominator here gives the sum of the constituents.

Field A can be the no of users passing through Flow A. Field B can be the no of users passing through Flow B. This formula will gives us how many people passed through which flow, This is import for A/B testing

Formula #3 & 4

This formulae compares the two fields and give a value which is not directly derived. For example consider a marketing SMS campaign. We can track the total number of the people targetted and the people replied to be put in DNC or Do not Contact list. Using this formula we can derive the actual number of people that responded back to the campaign or the actual response rate.

Visualizing Analytics For Custom Reports

In order to visualize the custom reports, you can click on the analytics tab and select custom reports

Facebook Ads

Messagingme.app Facebook Ads Payload Documentation

This document explains how to connect your Messagingme.app chatbot flow with buttons triggered by Facebook Messenger Ads.

Prerequisites

You need to have a Facebook Page connected to your Messagingme.app account.
Your Messagingme.app account needs to be connected to the Facebook Messenger platform.

Steps

Obtaining the Payload
Go to your Messagingme.app OmniChannel or Facebook Bot.
Navigate to “Tools” and then “Facebook Ads.”
Click “Create New Facebook Ads Payload.”

You can choose the subflow you want to connect to the user.

Click in “Edit” and copy the Payload displayed.

Additional Features

UTM Parameters: You can add up to nine UTM parameters to the Payload in Messagingme.app to track your Facebook Ads traffic and save automatically this information in Custom User Fields.

• Analytics: Messagingme.app provides a mini-dashboard to analyze data like clicks and user demographics from your Facebook Ads.

Create a Facebook Messenger Ads Campaign:

In Facebook Ads Manager, create a new campaign and select “Click to message” as the objective.
Choose Messenger as the message app and select the Facebook Page connected to your Messagingme.app account.

Set up your ad creatives (text, headlines, images) and choose “Send message” as the call to action.

Configure Message Template:

In the Message Template section, select “Partner App” and “Select Flow”

• Now you can select “Enter JSON Code”.

• Now you can paste your Messagingme.app Payload with your parameter if you have in “USER_DEFINED_PAYLOAD” and customize your template message.

Note

Ensure your Facebook Page and UChat account are connected.
Choose “Start conversation” in the Messenger Template.
Use “Partner App” and the Payload to link your UChat flow with buttons or quick replies.

Inbound Webhooks

Inbound webhook is a powerful tool to receive data from anywhere to the chatbot through a POST request.

With inbound webhooks, your bot can even start a conversation with a bot user who never talked to it before.

For example, when a client fills in their contact information on your website, you send the data to an inbound webhook of a chatbot, say an SMS bot. The SMS bot can then send a confirmation message to the client’s phone number.

If that webhook is built in a Voice bot, the bot can even call the client right away!

💡 Limitation - Each bot has up to 5 inbound webhooks, the rate limits is 500 request per 24 hours. Reset works as following:
24 hours after the first request. there is a timestamp in the response headers you can check.

The limit is per 24 hours, not per day, so it is not reset on fixed time

Create Inbound Webhook

It’s available in almost all channels, in your flow builder, go Tools - Inbound Webhooks:

Click on New Inbound Webhook, give a name and click Save:

You will see the editing interface like this:

Webhook Address

This area shows you where to send the data and the method, which is POST. Each inbound webhook has a unique URL in the whole Messagingme.app system.

Example of Received JSON

This area shows an example JSON for reference. It describes the structure of the data in the JSON we received later. We need it to find the values for both **user identification ** and data to save.

There are 2 ways to get an example JSON:

manually type/paste it here
listen to a real-time data from a live test

Values to Identify a User

Whenever the webhook receives data, it first checks the paths you specify here to see whether it can find an existing user in the chatbot.

If the user is not in the system, the chatbot will create a new profile. That’s how the chatbot initiates a conversation without talking to the user before.

However, some channels don’t allow the chatbot to start the conversation first due to privacy and spam issues.

For example, your SMS bot can send messages as long as you have the recipient’s phone number, while your Facebook Messenger chatbot cannot send messages to a Facebook user who never talked to your bot before.

Process for User Identification

This is the process of how the system identifies a user:

check user_ns
- if there is a valid user_ns, user found.
- if not, next step
check phone / email
- if we can find a user by the phone or email, user found.
- if not, next step
verify phone
- no user matched in the system, is the phone a valid number?
- if yes, user profile created.
- if not, webhook won’t be processed

Mapping Area

The mapping list shows which value should be stored in which custom field. When you get a sample JSON in the above area, click on Preview Payload to get a mapping tool.

Webhook Logs

Every single request is saved in Logs. Click on a record to see the received JSON data.

Inbound Webhook Limitation

By default, inbound webhook request limits is 500 request per 24 hours. You can see the limits from the screenshot below:

If you have exceed the limits, you do have the option to upgrade to more request per day, ask us to suscribe for more

Here is how you can find your flowNS,

Go to “All bots” in Messagingme.app dashboard, and then find the bot you want to increase the inbound webhook request limits, and then click the dropdown, you will find the flowNS.

How to debug inbound webhook max request error

First of all, if you are not receiving the data in the inbound webhook, or you can’t find the data in the logs, it’s highly possible that you reached the max daily request limits.

Here is how you can test it.

You can send the request to the inbound webhook from Postman or UChat external request, and then you can find the below information in the header:

As you can see, there is rate-limit-remaining, if it’s 0, that means you already reached the rate limits, you should upgrade for more limits.

Demo: Booking Confirmation

A perfect tool to test your inbound webhook is already built-in everywhere! Simple get a chatbot (whatever channel), test it in an Action Step.

Open another Messagingme.app webpage side by side, keep the inbound webhook editing on Page 1 and select an external request on Page 2:

Follow steps 1 to 8 in the following screenshot:

Provide the data that need to be sent to the chatbot and click Test, you must get a “webhook inactive” error since we haven’t activated it yet. It’s fine, click on Done on Page 1, and you will see the data saved:

Scroll down a bit, follow steps 1, 2, 3 to tell the system, where is the phone and email values in the JSON:

Finally, map the rest data to the chatbot:

Save your inbound webhook editing:

Enter the subflow, let’s send a message to the bot user:

Publish the flow and let’s do a live test in the external request again:

We can see that this time it run without error because we activated the webhook and used a real phone number. Go to Logs and we can see a new user profile is created successfully.

On the user side:

FAQ

Inbound webhook don’t works on your partner custom domain?

In cases where the inbound webhooks under your Partner custom domain stop working, while under Messagingme.app domain they are working correctly.

The issue could be inside your cloudflare settings.

Sometimes Cloudflare automatically detects requests to your domain and term them as attacks from bots. This blocks the requests coming to these inbound webhooks for a certain interval of time.

In order to avoid this, Go to your settings inside your Cloudflare dashboard, under the security tab, turn off “Bot Fight Mode”.

This will help you stop classifying requests made to your webhooks as bot attacks and your inbound webhooks will start working again

Note: Another reason webhooks can stop working is hitting their daily threshold. So always check to make sure the limits arent being maxed out

Smart Delays

Description

A new window has been added to the Tools section for Smart Delays. This feature allows you to view all users who are currently in a Smart Delay state. With this window, you can easily monitor and manage users paused in the flow, ensuring better visibility and control over active delays.

💡 Smart Delays will only be shown if the delay time is greater than 1 minute

How It Functions

Once a user passes through the Smart Delay action, their details will be displayed in the Tools section under Smart Delays. This allows you to easily monitor users who are currently under a delay and manage their status.

What we have in the Smart Delays:

Each Smart Delay has an ID assigned to it for easy identification and management.

Schedule Time: This field indicates when the Smart Delay will be lifted, showing the exact time when the delay will end and the bot will resume interaction.
Node: This indicates the node from which the Smart Delay was triggered, giving you context on where the delay originated in the flow.
Bot User: Here, you can see the bot user who is currently under the Smart Delay. This helps identify which users are affected by the delay at any given time.
Created At: This field shows when the Smart Delay was initiated, giving you insight into how long the user has been on delay.

You have the ability to cancel the Smart Delay for a particular user at any time, giving you full control to manage user delays as needed.

Use Cases

Follow-Up Messaging: You can use Smart Delays to send follow-up messages to users who showed interest in a product but left without completing the purchase. Trigger Smart Delays to send 3-4 messages over the course of hours or days, gently reminding them about the product, offering discounts, or suggesting related items.
Event Reminders: For users who have shown interest in an upcoming event (webinar, sale, product launch) but haven’t completed their registration or sign-up, Smart Delays can be used to send timely reminders. Messages can be sent before 10 hours 5 hours or an hour before the event to encourage participation.

Smart Delays are a great way to keep users engaged without overwhelming them. By using them strategically, you can send follow-up messages, reminders, and even re-engagement prompts at just the right time. Whether it’s reminding someone about an abandoned cart, following up after a purchase, or encouraging users to return after a while, Smart Delays help keep your interactions timely and relevant.

Important Note:

Smart delays work in a que based format when the delay is set higher than 1 minute. Queues are exectued once per minute so depending on when the smart delay has been triggered it could mean there will be an additional 1-2 minutes of delay added to the set total on the smart delay node itself

Broadcast

Use this feature to broadcast messages to your users! Just a few settings needed.

Go “Broadcasts” from the left sidebar, then click ”+ New Broadcast”.

To setup:

give a broadcast title (for yourself, not users)
select a sub flow
add conditions to filter who will receive this broadcast message

💡 TIP - to send to all users, try this condition “If User Id has any value”.

Filling in the rest settings like message type and time to send then click “Save”.

If you choose “Now” for the schedule, the message will be sent once you click “Save”. If not, you can cancel the broadcast anytime before it sent.

Here is also where you check broadcast history and data.

Max Users Per Minute Setting

Max Users Per Minute, allows you to adjust the number of users who will receive the broadcast message per minute. This can help in sending messages more gradually, making the broadcast appear more human-like and less automated.

New Feature: Max Users Per Minute

The Max Users Per Minute setting has been added to the broadcast feature. It allows you to control the delivery speed of broadcast messages.

Go to Create New Broadcast, Select any broadcast type that supports this feature.

Then, under the settings, choose the Max Users Per Minute option. The maximum value is 100 users per minute.

This feature is especially helpful if you want to avoid sending the broadcast too quickly to a large number of users. By slowing the process down, you can make the communication appear more gradual and humanized, improving the user experience.

Settings

General Settings

How to Access the General Settings Panel

To access the General Settings panel in Messagingme.app, follow these steps:

Enter Your Bot: Navigate to the specific bot you want to configure.
Go to “Settings”: In the left sidebar menu, click on “Settings”.
Select “General”: Within “Settings”, click on the “General” option.

Note: Only the workspace owner can configure this setting.

See the image below for visual guidance:

Bot Users Limit

Description: Sets the maximum limit of bot users. If the value is 0, there is no limit.
Access: Only the workspace owner can configure this setting. If a user does not see this setting, it means they are not the workspace owner.
How to Configure:
1. Navigate to the “Bot Users Limit” section.
2. Use the ”+” and ”-” buttons to adjust the user limit.
3. Click “Save” to save the changes.

Bot Users Auto Cleanup

Description: Automatically removes bot users who have not interacted within a specified period. If the value is 0, there is no cleanup.
How to Configure:
1. Navigate to the “Bot Users Auto Cleanup” section.
2. Set the number of days after which inactive users will be removed.
3. Add specific conditions if needed (e.g., delete users with certain tags).
4. Click “Save” to save the changes.

Notes:

If no specific conditions are set, users will be removed based on the last interaction time.

Paused Bot Automation Option

Description: Defines the behavior of automations and messages during the conversation pause.
How to Configure:
1. Navigate to the “Paused bot automation option” section.
2. Select one of the options:
  - Messages from agent, trigger and smart delay will be sent: During the pause, smart delay and triggers will continue to be working.
  - Only messages from agent will be sent: During the pause, only messages sent by the agent will be sent; all automations, triggers and smart delays will be stopped.
3. Click “Save” to save the changes.

Bot Start Flow

Description: Sets the default start flow of the bot.
How to Configure:
1. Navigate to the “Bot Start Flow” section.
2. Select the desired default flow (default is “Main Flow”).
3. Click “Save” to save the changes.

Live Chat Settings

Livechat settings can be accessed by clicking on the settings tab inside the bot, then clicking on the live chat.

Overview

Here you will find all the settings related to livechat. You will also find settings for closing notes as well as agent notifications.

Conversation Visibility

The Conversation Visibility feature allows you to control which conversations live chat agents and members can view in the system. This setting is essential for managing access and work distribution among your team.

How to Access

To configure conversation visibility:

Go to Settings in the chatbot main menu
Navigate to Live Chat
Locate the Conversation Visibility section

Visibility Options

1. All Conversations (Default)

Description: All agents have access to all available conversations
Who can see:
- Owners and Admins: Always see all conversations
- Supervisors: See all conversations
- Agents: See all conversations

2. Only Mine (Assigned to Me)

Description: Agents only see conversations assigned directly to them
Who can see:
- Owners and Admins: Always see all conversations
- Supervisors: See all conversations
- Agents: Only conversations assigned to them individually

3. Mine + Unassigned

Description: Agents see their conversations and those without assignment
Who can see:
- Owners and Admins: Always see all conversations
- Supervisors: See all conversations
- Agents: Conversations assigned to them + unassigned conversations*

Unassigned conversations are those not designated to any specific agent or agent group.

4. Mine + My Groups

Description: Agents see conversations assigned to them and to groups they belong to
Who can see:
- Owners and Admins: Always see all conversations
- Supervisors: Only conversations from groups they belong to
- Agents: Conversations assigned to them + conversations from their groups

5. Mine + My Groups + Unassigned

Description: Combination of previous options
Who can see:
- Owners and Admins: Always see all conversations
- Supervisors: Conversations from their groups + unassigned conversations
- Agents: Conversations assigned to them + conversations from their groups + unassigned

Additional Group Settings

Visibility Within Agent Groups

When configuring an agent group (in Workspace Settings > Agent Groups), you can set additional visibility:

All Conversations: Agents see all conversations assigned to the group
Only Conversations Assigned to Me: Agents see only group conversations specifically assigned to them

Supervisor Settings

Supervised Agents

For supervisors, there is an additional setting:

Access the three-dot menu next to the supervisor
Select Supervised Agents
Choose which agents will be supervised

Result: The supervisor will see all conversations from selected agents, enabling targeted monitoring and support.

Permission Hierarchy

Role	Access
Owner	Always sees all conversations, regardless of settings
Admin	Always sees all conversations, regardless of settings
Supervisor	Access varies according to selected configuration
Live Agent	Limited access according to visibility configuration
Member	Same restrictions as agents

Important Notes

Changes to visibility settings require a page refresh to be applied
Owners and Admins always maintain full access, regardless of settings
Group settings take priority over general settings when applicable
Unassigned conversations include those without a specific agent or group designated

This documentation reflects all the visibility features in the live chat system.

Live Chat Features

Following options can be accessed under these:

Settings	Explanation
Disable Enter Key to send message	By default pressing Enter Key sends a message inside livechat. You can disable this to let Enter key change the cursor to a new line
Disable Reassign conversation by agent	Enabling this setting will stop agents from re-assigning a conversation from them to another agent and vice versa
Any incoming messages reopen the conversation if status is Done or Pending	Enabling this will allow any reply coming from the user to move into Open status regardless if it’s Pending or Done.
Hide Icon - User Tags	Hide User Tags from live chat bot user overlay
Hide Icon - Labels	Hide Labels from live chat bot user overlay
Hide Icon - Subscribed Sequences	Hide Subscribed Sequences from livechat bot user overlay
Hide Icon - Shop Orders	Hide Orders from live chat bot user overlay
Hide Icon - Calendar File Generator	Disable generating Calendar file from live chat icon tray
Hide Icon - Send Subflow	Disable sending subflows from live chat icon tray
Hide Icon - Agent Assist	Disable Agent Assist from live chat icon tray
Show Icon - Custom URL	Enables Custom URL feature on live chat icon tray
Hide System Message - All	Hides System Messages from Live Chat for all workspaces members
Hide System Message - Live Chat Agent, Live Chat Supervisor	Hide System Messages from agents and supervisors only
Enable Closing Notes	Enable closing notes for agents
Closing Note Category Is Mandatory	Mandates agents to enter closing note category when moving to Done
Prepend Agent Name To The Message Send By Agent (Whatsapp)	On Whatsapp, Name of agent is prepended when a messages sent from agent
Show only last 4 digits from phone number in livechat - Livechat agent, Livechat supervisor	Masks the phone number of users with *s with only last 4 digits visible. This filter applies to agents and supervisors only. Main usage is privacy from agents

Prepend Agent Name for Web Chat and WhatsApp

Overview

The Prepend Agent Name setting in Live Chat allows agents’ names to appear before each message they send when taking over the chat. This helps customers easily identify which agent they are speaking with, creating a more personalized and transparent communication experience.

Purpose

When agents take over a live chat, it can sometimes be unclear to customers which agent is responding. By enabling this setting, the agent’s name will automatically appear at the beginning of each message, helping customers recognize who they are interacting with during the conversation. This feature improves customer trust and enhances clarity.

Steps to Enable “Prepend Agent Name” Setting

Access Live Chat Settings:
- First you must access the bot that you let enable this feature within UChat.
Locate the Live Chat Settings:
- Navigate to Live Chat Settings under the Settings menu.
- Look for the option titled Prepend Agent Name.
Enable the Setting:
- Toggle the switch to enable the Prepend Agent Name option.
- Once enabled, all messages from agents in a live chat will display the agent’s name at the start of each message.
Save Changes:
- After enabling, make sure to save the changes for them to take effect in active web chat sessions.

Example

Here’s how the messages will look when the Prepend Agent Name option is enabled:

Without Agent Name Prepending:
- Message: “Hello, how can I assist you today?”
With Agent Name Prepending:
- Message: “John Doe: Hello, how can I assist you today?”

In the second example, the agent’s name “John Doe” appears before the message, clearly indicating to the customer who is responding.

Additional Notes

Availability: This setting is only available for web chat and WhatsApp.
Use Case: This feature is especially useful in environments where multiple agents may take over a single chat session, ensuring customers can follow who is assisting them.

Custom URL

Here you can set a custom url for the bot user, that when clicked will open a certain third-party platform with that bot user’s details.

This feature is heavily used with CRMs, and enables agents to open their CRM from within Messagingme.app in an iframe and edit bot user’s information directly inside their CRM from one screen without having to leave Messagingme.app.

The URL is entered as well and a system variable can be selected from the given options below. You can also choose the desired window size of iframe from the Target Drop down.

Make sure that the Custom URL Icon is enabled in the icon tray.

Go to livechat, click on a conversation and you will see the custom URL icon. Clicking on it should open popup.

Note: Make sure your CRM allows iframe or popup modals, otherwise the feature may not work

Live Chat Integration

Here you can select the platform where you want to transfer the livechat once the bot automation is paused. Following platforms are supported

Note: Make sure the platform of your choice is already integrated with UChat inside the integrations section of the workspace

Live Chat Auto Pause Minutes

This feature allows you to set the minutes for auto pause whenever an agent takes from automation.

This is the timer that runs during which the bot automation is paused.

Live Chat SMS Sender

This feature allows you to select the phone number from which you want to send SMS to bot users from livechat. The numbers must be connected in your Twillio/Telenyx account inside the integrations section of the workspace.

Live Chat Email Profile

This feature allows you to select the email profile from which you can send emails directly from Livechat. The email must be connected under the SMTP section of integrations of the workspace.

Live Chat Desktop Notifications

This feature allows you toggle the configuration for notifications. You can choose when to get notified. This is only confined to the Web app desktop notifications when using a browser.

Single Sign-On (SSO)

Single Sign-On (or SSO) provides us the ability to have one master bot user, which syncs the data between all of your bot users in different channels. This helps vastly in syncing data and identifying bot users when multiple channels are involved.

You can enable SSO by going inside the “Settings” tab on the bottom-left of your Flow builder side menu. Then clicking on the “SSO Settings” option.

Click on the “Basic” tab and fill in the required details.

Once done, Create a new sub-flow. Here we will set up the SSO logic.

Once SSO is enabled, you will start seeing “SSO Required” in the Start nodes of the sub-flows. Enabling this option will direct the user toward the SSO login and then redirects the user to the sub-flow you selected inside the settings upon successful login.

Once successful, the “Thankyou” screen will persist for 5 seconds and then the user will be redirected to the follow-up subflow, or you can manually exit the page as well.

Advanced Settings For SSO

Advanced options enable you to set up your own logic flows for SSO. This enables the user to setup the SSO in channels where buttons with links are not properly populated by using a system variable field called “SSO Url”

Syncing Of Data Between Users

The bot user with the SSO tag is the master user which syncs the data between the same bot user in different channels.

If you add a tag or change the value of a variable for the SSO user, the change is also done for bot users in other channels.

If you add a tag or change the value of a variable for the bot user in other channels, the change is also done for the SSO user.

This allows users to sync data between multiple channels across bot users and gives more flexibility when working over multiple channels.

💡 The bot users are still counted separately. SSO only functions to sync the data between bot users, it does not accumulate the bot users into one bot user.

Customizable Thank You Page

You can now customize the text on the thank you page as per your desire. The default text will be “thank you”. This feature is available in both Basic and Advance SSO modes.

Rate limit Setting

Rate Limit is a valuable addition to the chatbot system, providing administrators with a streamlined approach to managing user interactions.

You can find in flow, goto action node -> Advance Actions -> Rate Limit Attempt

Use Cases for Rate Limit

Limiting API Calls:

Ensures compliance with third-party platform restrictions.

Controls the number of API calls per user within a specified time frame.

Preventing Fake Orders

Helps to mitigate fraudulent orders in e-commerce settings.

Restricts the number of orders a user can place within a specific time frame.

Controlling Notifications

Manages the frequency of notifications sent to users.

Ensures users are not overwhelmed with excessive notifications, particularly in e-commerce order updates.

In summary, Rate Limit is a valuable addition to the chatbot system, providing administrators with a streamlined approach to managing user interactions while ensuring compliance with external platform restrictions and preventing abuse of system resources.

Flow builder

In this section anything you need to know about building a flow

If you want more precision about building blocks (send nodes, quesiton nodes, action nodes,…) please refer to the next section building blocks & steps

Flow builder overview

Channels, Sub Flow and Step

Channels

SubFlow type

Step type

Flow labels

Creating a Label and Assigning Color

Adding a Sub-Flow to a Label

Adding a Sub-Flow to a Label

Accessing Sub-Flows by Labels

Managing Sub-Flows in Folders with Flow Labels

Bulk Actions for Flow Label Management

Field

User field

Bot field

System field

User Id in Different Channels:

Variable Type

Boolean Value

Create Custom Field

Create Custom Field in Contents Section

Create Custom Field in Question and Action Step

Publish Version & Draft Version

From Publish Version to Draft Version, 1 way:

From Draft Version to Publish Version, 3 ways:

Navigation Bar, Sidebar & Flow Builder

Navigation Bar

Sidebar

Flow Builder

Change Themes

Hide Mini-map or Tooltips

Basic Operations to Build Flows

Edit step

Connect Steps:

Select Multiple Steps (Move to Canvas/Sub Flow)

Copy and Paste Steps

Sub Flows

Workflow

Create Workflow

Workflow Example

Trigger Workflow

Function flow

Create Function Flow

Function Flow Example

Call Function Flow

Multiple Outputs

Analytic

Message Reports

Steps to Access

Available Report Types

Messages

Line Charts

Sent Messages:

Usefulness of the Charts

Analysis of Agent Messages, Private Notes, and Emails

Agent Messages

Private Notes

Emails Sent

Emails Opened

Usefulness of the Charts

Conversations

Conversation Overview

Usefulness of the Chart

Below is a visual example of the chart:

Opened vs. Closed Conversations

Usefulness of the Chart

Below is a visual example of the chart:

Heatmap of Opened and Closed Conversations

Heatmap of Opened Conversations

Heatmap of Closed Conversations

Below is a visual example of these charts:

Opened Conversations by Type

Opened Conversations by New and Returning Users

Below is a visual example of these charts:

Closed Conversations by Type

New and Returning Closed Conversations

Below is a visual example of these charts: