Optimizing your AI agent performance

Optimize the performance of your AI agent by using analytics to identify opportunities for improvement and by building smarter dialogues.


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Optimize the performance of your AI agent by using analytics to identify opportunities for
improvement and by building smarter dialogues.
This article covers the following topics:
Using analytics to improve the AI
model
Using smarter dialogues to improve user
experience




Using analytics to improve the AI model

Use analytics to learn where you can improve AI agent understanding and the deflection
rate.
This section covers the following topics:
Improving deflection rate
Reviewing other key metrics




Improving deflection rate

Any conversation that doesn’t end in escalation is considered deflected. Review
conversations that were not deflected and take steps to improve your deflection rate.
Read through conversation logs to see how well your dialogues
work, looking for the following:

Broken dialogues: A user might break a dialogue by not using the buttons provided,
or by asking about their order number in the middle of the escalation flow. Consider
including free text to guide users through the flow.

Misunderstanding instructions: Users generally don’t always read
long messages. Consider making the message shorter and easier to follow.


Missing information: The user may lack key information to help
them through the flow. In that case, think about what a live agent would do and add
as much of that information in the dialogue as possible.


Take the following actions to improve deflection:

Adjust the default reply: Manage expectations and guide users through flows.
See About system replies for AI agents.

Use content coverage analysis: Identify potential new use cases that can be
automated. See Performing content coverage analysis.

Use an API integration: Identify suitable use cases for an API
integration to automate more conversations. See Preparing to create a custom integration.


After taking steps to improve your deflection rate, review resolution states as another way to improve your AI agent
performance. Filter conversation logs by custom resolution to review escalated and
unresolved conversations. Look for trends over time.




Reviewing other key metrics

In the left sidebar of the AI agent, click Reporting for additional key metrics. To
optimize the AI agent’s performance, focus on the following metrics:
Total conversations as compared to Understood conversations
Assisted conversations and Handled conversations as compared to Escalated
conversations
Automated resolutions

For more, see Analyzing AI agent performance with the Reporting
dashboard.



Using smarter dialogues to improve user experience

Use the following tools to create smarter dialogues and improve your customers’ experience
with the AI agent:

Backend integrations: Use backend integrations where possible to fetch data that the AI
agent can provide to users.

Conditional blocks: Use conditional blocks to jump into another flow based on certain
keywords. This provides a more streamlined conversation before escalation if the user
has been through the flow before.

Escalation templates: Streamline replies by managing the escalation
process in one centralized template, rather than in each specific flow. Set operating hours to manage expectations and escalate appropriately.

A/B testing: Use A/B testing to optimize dialogue flows with
data-driven decisions. See Performing A/B
testing for AI agents.




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