Best practices for creating answer flows in an AI agent (Legacy)

After youcreate AI agentfor a messaging channel, there are a number of best practices regarding answer flows that can make your AI agent more effective.


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This article describes functionality that moved into legacy
status on February 2, 2025. On December 31, 2026, this functionality will no longer
be available. For more information, see this announcement.

After you create AI agent for a messaging channel, there
are a number of best practices regarding answer flows that can make your AI agent more
effective.
This article contains the following sections:


Planning your answers
Building answers
Improving answer-to-question matching




Planning your answers

Before you start creating answers for your AI agent, consider these planning best
practices:

Identify questions that users ask regularly. Look at your top ticket
issues, review common help center search terms, and talk to your agents to
plan answers you want to create for the AI agent.

Create answers first for questions that can be resolved on their own
and don’t need an agent to take action. Examples of common, easily-answered
questions might include:
Operating hours
Reset password
Store locations



Start by answering the most common questions first. It's a
good idea to have answers for about 20 of your most common questions, then
build up coverage over time. Don't try to address every issue right
away.





Building answers

As you create your answers for your AI agent,
consider these best practices for how to structure your answers for better
performance.


Engaging the user

When you are thinking about the start of your answer to engage the user, keep
these best practices in mind:



Start each answer by echoing the user's issue back to them. This
reduces the risk of confusion if the Ai agent matches to the wrong
answer. For example, if a user enters "Cancel my account," the AI agent
response should be, "Sorry to hear you want to cancel your account."

Help end-users understand how they should navigate the AI agent.
Depending on how the AI agent is designed, different end-user
interaction styles can impact the AI agent's performance. Make it clear
to the user how they should navigate the AI agent to find answers.

Ask the user to select from provided options
throughout the answer, if the AI agent is designed to provide a
navigation experience (one large answer flow).

Create a separate agent transfer answer to enable the
user to contact support. Link the agent transfer
answer throughout the main navigation experience as
an alternative option if the presented options aren’t what the
user needs.



Create separate answers to handle small talk. For example, you
might create a sign off response, such as "Thanks, goodbye."





Finding a solution

As you build the answer to guide the user to a solution, keep these general best
practices in mind:



Avoid building out overly complex flows to specific articles.
Instead, leverage generative replies to automatically return an answer.
This helps minimize answer maintenance for your.

Personalize your customer experience. Create personalized
experiences by requiring authentication,
including conditional
scenarios, or using intents.

Create autonomous actions for the user by making an API call to another
system. Doing so, you can automate a majority of user requests, such as
making a return, from end-to-end.

Provide a resolution to ensure each answer addresses a question.
For example, state the answer to the question in an AI agent message,
provide a link to a help article, or perform a task with an API
call.





Closing out the conversation

When you are thinking about the end of your answer and how to close it out, keep
these best practices in mind:



Ask for feedback to confirm the user's problem has been resolved.
You can ask if question was resolved
to ensure the user's issue is revolved. You can also use this feedback
to analyze AI agent effectiveness later.

Provide
alternative options to eliminate dead ends.

If an API call fails, provide an option to
transfer to agent or
link to related
answers. For example, if an order status retrieval
fails, provide a link to an article about how users can manually
check their order status.

If you ask for feedback, and the user indicates
that the problem has not been solved, provide alternative
options. Consider adding an option to transfer to agent or link
to related answers that might help.

If a user contacts you outside of business hours,
provide an escalation option to transfer to agent, so the user
can create a ticket and an agent can respond later
asynchronously.








Improving answer-to-question matching

You can improve the chances of the AI agent suggesting the right answer or article to
a user by manually adding training phrases or by assigning intents to answers. To
use intents, you must have an intent model assigned.


Using training phrases

You can use training phrases in answers to
improve the AI agent matching performance. If you have an intent model, you
should use intents instead of training phrases.
When you use training phrases, keep these best practices in mind:



Make note of how users word common questions and use similar
language in training phrases for the answer.

Group common topics together in one answer. For example, include
international shipping and domestic shipping in one answer.

Use phrases with similar or related meanings. Zendesk AI utilizes
a model that employs semantic matching, where the model considers the
overarching meaning of the question. For example, "solar power" and
"renewable" are semantically related, and the model can recognize this
connection. The model may also suggest two texts as a match if they are
likely to co-occur, such as "credit card" and "bank account."

Add a variety of phrases to improve the match rate.
However, you don’t need to add every single variant for how the
question might be asked. For example, a user might misspell something
or phrase it a little differently and still get a match.


Aim for a minimum of 3-5 training phrases for each
answer.


Avoid adding single words. AI agent training works best
with short, multiple-word phrases that provide enough details for
context. For example, use “Refund order” instead of “Refund," or use
"Renew membership" instead of "Renew."

Avoid using unnecessary words and generic phrases
such as "Hi" or “I want to” or "How do I." These can dilute the
question's core meaning. For example, instead of "Hi, I want to get
a refund," use “Get a refund."


Do not add training phrases in multiple languages. Training
phrases are auto-translated, if enabled.





Using pre-trained intents

If you have an intent model, you can assign pre-trained intents to answers instead
of manually adding training phrases. When you use intents, keep these best
practices in mind:



Assign pre-trained intents to answers to significantly improve
the question-answer match performance.

Use generative replies for intents that are frequently asked
questions. These common questions can typically be resolved by
the AI agent using information from your help center articles.





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