Workflow recipe: Using an AI agent to collect customer info and immediately escalate to a human agent

When a customer reaches out for support on a messaging channel, you can configure
an AI agent to collect their information and immediately escalate the conversation
to a human agent. Use this workflow if you want human agents to provide customer
support instead of letting an AI agentrespond with AI-generated replies.



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Note: If you previously configured
a
default messaging response
on your messaging channel,
follow the instructions in this article to implement the same functionality
using an
AI agent.



When a customer reaches out for support on a messaging channel, you can
configure an AI
agent to collect their information and immediately escalate the conversation
to a human
agent. Use this workflow if you want human agents to provide customer
support instead of
letting an AI agent
respond with AI-generated replies.

This article contains the following topics:


Understanding the workflow


Step 1: Create an AI agent


Step 2: Create a configured action to check the customer’s authentication status


Step 3: Create a form template to collect the customer’s information


Step 4: Set your business hours in your AI agent


Step 5: Edit the welcome reply


Step 6: Test, activate, and validate




Understanding the workflow


Even if you want human agents to provide support to your customers,
you can still
benefit from an AI agent. You can configure an AI agent to:



Greet customers: Every time a customer
begins a conversation with your AI
agent in the Web Widget, the AI agent’s first response is the
welcome message
you configure.


Collect information: The AI agent
presents the customer with a form to be
filled out. You can configure this form to collect whatever information
your
human agents will need to solve the customer’s request, such
as details about
the issue or the customer’s contact information. This saves your
human agents
time because they already have the necessary information to act
on customer
requests by the time the requests reach them.


Escalate requests: The AI agent
tells the customer that their request is
being sent to your support team. Behind the scenes, human agents
are notified
that a support request has been received, and they can accept
the request and
begin responding to the conversation.



Optionally, you can also configure the AI agent to behave differently
depending on:



Your business hours:


During business hours, the AI agent can escalate the
conversation to a
human agent on a messaging channel, where the agent can
immediately
begin conversing with the customer.


Outside of business hours, the AI agent can collect the
customer’s
information and escalate the request as an email ticket
to your support
team.




Customer authentication status:


If the customer is authenticated, the AI agent won't
collect the email
and name in the form. However, any other information
that needs to be
collected can be.


If the customer isn’t authenticated, you can collect
their email and
name in addition to any other information that needs
to be collected.





This workflow utilizes the AI agent welcome reply, which is a default
system reply
that’s sent to the customer at the
beginning of a conversation. You’ll edit the dialogue associated
with this reply to
contain the AI agent messages, actions, and forms needed to carry
out the workflow
described above.



Note: If you set up an AI agent
as described in this article,
this workflow does not consume paid
automated resolutions.
However,
automated resolutions can be consumed if you add additional configuration
to the
AI agent, like
connecting knowledge sources
or
creating use cases.





Step 1: Create an AI agent


First, you need to create the AI agent that converses with customers
on your
messaging channel.

To create an AI agent


Follow the step-by-step instructions in
Creating an AI agent to automatically resolve
customer issues.




Important: After you create
your AI agent,
disconnect the help center
that was
automatically connected during the creation flow, and make sure
you did not add
an external knowledge source. Also, make sure you
do not create any use
cases. AI agents with connected knowledge sources and use cases
can incur paid
automated resolutions.






Step 2: Create a configured action to check the customer’s authentication
status



Next, create a
configured action
that checks the customer’s
authentication status. This information is available through the
Sunshine
Conversations
app user
object. The
Get user
CRM action gets the user’s
authentication status and saves it as a session parameter for the
conversation.



Tip: For more information on how
authentication
works, see
Understanding user authentication for
messaging.



To create a configured action to check authentication status




In the AI agents workspace, select the AI agent you want to work
with.


Click
Actions in the sidebar, then select Configured actions.


Click Create configured action.


In Name, enter a descriptive
name for the action, such as
Get
customer authentication status, name, and email.


In Target, select
Sunshine Conversations.


In Task, select
Get user.


In Field to retrieve, select
authenticated.


In Save as parameter, enter
the name of the parameter the value
should be saved as, such as authenticated.


Click Get another field and
add parameter information for the
customer’s name:


Field to retrieve:
givenName


Save as parameter:
name




Click Get another field and add parameter information for
the customer’s
email:


Field to retrieve:
email


Save as parameter:
email




Click Create.

When you add this action in the welcome reply
dialogue (described below), the AI agent will fetch the
indicated fields
from the app user object and save it as session parameters.






Tip: You can find additional
optional
configuration for this action in the
developer documentation.









Step 3: Create a form template to collect the customer’s information



Create a form template to specify which details to collect from the
customer.


Based on their authentication status, the form collects the missing
details. For
example, an authenticated user means their email is known to be authenticated
in the
first place, so there’s no need for the form to collect the email
again.


You should create two different form templates, one for authenticated
customers and
one for unauthenticated customers. The form for authenticated customers
doesn’t need
to include fields for Name and Email, since those details are already
known due to
the authentication, but it should include fields for any other details
you want to
collect. The form for unauthenticated customers should include Name
and Email, in
addition to any other details you want to collect.


Which form template is shown to the customer depends on their authentication
status.
You’ll configure this when you edit the welcome reply’s dialogue,
described later in
this article.


To create a form template



Follow the step-by-step instructions in
Creating a form template.





Step 4: Set your business hours in your AI agent


Set operating hours in your AI agent that mirror your business hours.
Operating hours
define the working hours for your human agents.





To set your business hours



Follow the step-by-step instructions in
Setting operating hours.





Step 5: Edit the welcome reply


The last setup step is to edit the dialogue associated with the welcome
reply. The
dialogue contains the AI agent messages, actions, and forms needed
to carry out the
workflow described above.

To edit the welcome reply



In the AI agents workspace, select the AI agent you want to work
with.


Click
Content in the sidebar, then select Use cases.


In the list of use cases, select
Welcome reply.

Select the reply for the language you want to edit.

Click Edit dialogue.
The dialogue builder opens.


(Optional) If you have separate default messaging responses
for different
channels, click the plus (+) icon above the initial AI agent
message block,
select Conditional, and enter
integrationID in the empty
field.


In the child Parameter block, select
is in the first field
and enter your first channel’s integration ID in
the second field.


Click the plus (+) icon under the Conditional field
to add and
configure additional Parameter blocks as needed for
your other
channels.

Tip: You can make
it
easier to see in the
conversation logs
which channel’s dialogue branch was followed
during a
conversation. First,
create an action
that
adds a label with the channel’s name. Then,
add the action
to each
parameter block.





Click the plus (+) icon above the initial AI agent message
block and select
Availability.


In the Availability block, click
Select rule and select the
operating
hours rule you created above.


Under the Open block:


Click the plus (+) icon, select
AI agent message, and
enter
what the AI agent should say to the customer at the
beginning of a
conversation when human agents are available.


Click the plus (+) icon underneath the block you
just added, select
Conditional, and enter
authenticated in the
empty
field.


In the Parameter block, select
Is (boolean) in the
first
field and True in the
second field.


Click the plus (+) icon underneath the block you
just added, select
AI agent message, and
enter the template shorthand for
the authenticated users form.

For help finding the template
shorthand, see
Adding a structured message
template in a dialogue.



Click the plus (+) icon underneath the block you
just added, and
select Escalation.


In the first field, enter what the AI agent
should say to
the customer when escalating them to a human
agent.


In the second field, select
Forward to an agent.




Click the plus (+) icon underneath the Fallback block,
select
AI
agent message,
and enter the template shorthand for the
unauthenticated users form.


Click the link icon underneath the Fallback block
and then select
the Escalation block to link the two blocks together.




Repeat step 9 for the Closed block to reflect what should
happen when human
agents aren’t available.

At this point, your dialogue should look
similar to the following:






Click Publish.




For additional help with the dialogue builder, see
Creating dialogues to define scripted conversation flows for AI
agents.




Step 6: Test, activate, and validate


After your AI agent is configured as you want, you should perform
three last tasks:



Test the AI agent before making it live for customers.

See
Testing conversation flows in AI
agents.



Activate the AI agent on the channels you want it to work on.

See
Activating and managing AI agents.



Validate that AI agent conversations are appearing in the conversations
log.

See
Reviewing conversation logs for AI
agents.






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