Migrating AI agents from chat to messaging


Configuring chat channels for AI agents is no longer recommended. Instead, you should migrate your AI agents to work on messaging channels. This article walks you through the migration process.


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Configuring chat channels for AI agents is no longer recommended. Instead, you should
migrate your AI agents to work on messaging channels. This article walks you through the
migration process.
This article contains the following topics:

Before you start
Step 1: Clone your AI agent
Step 2: Update your AI agent’s configuration
Step 3: Test your AI agent’s conversation flows
Step 4: Finalize and launch your AI agent on messaging channels
Step 5: Monitor your AI agent’s performance



Before you start

Before you start, keep the following requirements and considerations in mind.


Requirements

To successfully migrate an AI agent from chat to messaging, you’ll need:

The client admin role in the AI agents
workspace
A sandbox environment with Web Widget set up

(Optional) Access to your website and/or app's source code
This is required only if you want to configure more complex
automation using actions than is available by default.






Considerations

When migrating an AI agent from chat to messaging, you may wish to consider
creating multiple AI agents for different types of messaging channels. For
example, you might want to have one AI agent for web-based messaging and another
for social messaging (such as WhatsApp).
The reason for this is that request types and communication styles differ
depending on the channel a customer reaches out on. In addition, which features
are supported depends on the messaging channel. See Getting started with social messaging
for more information on the available channels.




Step 1: Clone your AI agent

To ensure there's no disruption in your customer service, clone the AI agent you want to migrate.
The original AI agent will stay active on your chat channels until you’ve completed
the steps below and are ready to launch your migrated AI agent on messaging channels
instead.


Note: Analytics and other historic data are not
transferred from the original AI agent to the cloned AI agent.




Step 2: Update your AI agent’s configuration

In the cloned AI agent, you should review and adjust the forms, actions, and
escalation strategy to ensure they work on messaging channels.
This section contains the following topics:

Step 2.1 Recreating the pre-chat form
Step 2.2: Reviewing and adjusting actions
Step 2.3: Re-evaluating your escalation strategy
Step 2.4: Creating tickets for AI agent–handled requests



Step 2.1 Recreating the pre-chat form

The pre-chat form isn't available on
messaging channels. If you still want to collect information from the customer
before the AI agent conversation starts, you’ll need to recreate the form. See
Using and sanitizing forms in conversation
flows for AI agents.


Tip: Customers are more likely to drop off if
asked to provide a lot of information immediately upon entering a
conversation. It’s recommended to design your conversation flows to allow
customers to ask their questions first, and use a form to collect user
information only if the conversation needs to be escalated.




Step 2.2: Reviewing and adjusting actions

Not all actions that are available on chat channels are available on messaging
channels. Review the actions you created for
your AI agent and adjust them as needed.
The following table summarizes the actions available on chat channels compared to
messaging channels. The icon means an action isn’t available by default and
requires additional configuration.









Chat action
Messaging action


Get customer info
Get user


Update customer info
Update user


Get tag



Add tag

Add user tag
Add conversation tag
Overwrite user tag
Overwrite conversation tag



Trigger reply
Trigger reply


Leave channel






For more information on the actions available for messaging, see Available CRM actions for AI agents and
Sunshine Conversations.
If there’s information you want to continue using that’s not available by
default, you’ll need to customize the Web Widget snippet to capture it. See
Using messaging metadata with the Zendesk Web
Widget and SDKs.


Get customer info

This action allows you to retrieve visitor information on Zendesk. This
information can then be saved to personalize your messages or create reply
variations.
The table below compares the specific customer info that can be retrieved and
used in dialogues in chat and messaging. The icon means an action isn’t available by default
and requires additional configuration. The icon means the information can be defined in
your Web Widget code. For help, see the following articles:

Using messaging metadata with the
Zendesk Web Widget and SDKs
Setting up user authentication for
messaging
Custom Web Widget initialization
behavior












Customer info

Chat “Get customer info” action
details
Messaging “Get user” action
details


Name



Display name (what users enter in the pre-chat
form)






Given name


Surname





Locale



Current region


Current country


Current city






Locale in BCP 47
format





Email




External ID




Phone




Notes




Status




Device




Tags




Avatar URL




Metadata










Update customer info

This action allows the AI agent to fetch the information visitors offer
during a conversation and update it on the visitor's Zendesk ticket.
The table below compares the specific customer info that can be retrieved and
used in dialogues in chat and messaging. The icon means an action isn’t available by default
and requires additional configuration. The icon means the information can be defined in
your Web Widget code. For help, see the following articles:

Using messaging metadata with the
Zendesk Web Widget and SDKs
Setting up user authentication for
messaging
Custom Web Widget initialization
behavior












Customer info

Chat “Update customer info” action
details
Messaging “Update user” action
details


Name



Display name (what users enter in the pre-chat
form)






Given name


Surname





Locale


Ccurrent region

Current country


Current city






Locale in BCP 47
format





Email




External ID




Phone




Notes




Status




Device




Tags

Update Sunshine tag


Avatar URL




Metadata




Priority




Organization ID




Group ID




Assignee ID




Brand ID










Get tag

This action allows you to pull existing tags from chat into an AI agent. The
Get tag action doesn’t exist for messaging.
However, you can add tags as part of the conversation metadata. The AI agent
can access these tags through the Get conversation action, where the
Field to retrieve value is set to (Metadata). You then
need to add a code snippet to the Web Widget. The action requires a prefix
of "zen:ticket:tags": to retrieve tags successfully. See
Setting conversation fields and
tags.



Add tag

This action adds custom tags to a chat which can give you insights into your
tickets.
On messaging, there are four tag-related actions:

Add user tags
Overwrite user tags
Add conversation tags
Overwrite conversation
tags




Trigger reply

This action stays the same. See Triggering a reply when a conversation
starts or becomes inactive.



Leave channel

This action is used to show the queue position to
customers for chat and isn't available for messaging.




Step 2.3: Re-evaluating your escalation strategy

Migrating from chat to messaging presents an opportunity to re-evaluate your
escalation strategy. For more information, see About escalation strategies and flows for AI
agents.



Step 2.4: Creating tickets for AI agent–handled requests

With chat, you could automatically create a ticket in
Support when a chat ended and attach the transcript. To create the
same result in messaging, it’s recommended to use the AI agent ticket feature, which
automatically creates tickets for messaging conversations that were handled
entirely by your AI agent.




Step 3: Test your AI agent’s conversation flows

After you’ve updated your AI agent’s configuration, the next step is testing. Before
going live, perform thorough testing to ensure all conversation flows work as
intended. See Testing conversation flows in AI agents.



Step 4: Finalize and launch your AI agent on messaging channels

Finalizing and launching your AI agent consists of the following tasks:


If you cloned your AI agent to a sandbox environment and made any updates to
the sandbox Web Widget code, make sure to update the production Web Widget
code to match, including any metadata, user authentication, or tags.
Update the IDs of any build items to make sure they point to your production
subdomain, not your sandbox domain. You’ll need to do this for:

Actions: See Editing an action.

Transfer groups: See Managing messaging channel
settings for an AI agent.

Forms: See Using and sanitizing forms in
conversation flows for AI agents.



Set your AI agent as the default
responder on the messaging channels of your choice.





Step 5: Monitor your AI agent’s performance

The final and ongoing step is to monitor your AI agent to ensure everything is
working as intended. See Analyzing AI agent performance with the reporting
dashboard.


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