> ## Documentation Index
> Fetch the complete documentation index at: https://docs.athina.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Query Topic Classification

<video autoplay controls muted loop playsinline className="w-full aspect-video" src="https://info.athina.ai/videos/topic-classification.mp4" />

When you log inferences with a `user_query` field, we can automatically run query topic classification against every logged inference.

Athina segments your data based on these query topics to show you granular analytics and comparisons.

Alternatively, you may log the topic manually. [Learn more](/api-reference/logging/logging-attributes)

### Configure Query Topics[](#configure-your-topics)

You can configure your topics in your [Settings ](https://app.athina.ai/settings) page.

Currently, we will categorize each user query into a single topic label.

So it is best to configure non-overlapping topics.

<Tip>
  **Example Topics**

  * Product Question
  * Refunds
  * Order Status
  * Exchanges
  * Complaints
  * Product Availability
  * Shipping
</Tip>

### Explore your data, segmented by topic[](#explore-your-data-segmented-by-topic)

When you apply a topic filter on the [Observe ](https://app.athina.ai/observe) page or the [Analytics ](https://app.athina.ai/dashboard) page, the usage and performance metrics will also update to only include inferences labeled with the selected topic.

This can help you narrow down to only look at inferences that were categorized into a certain topic.

<Info>
  **Example**: you may find that your model's pass rate is 85% for Product
  Questions, but only 68% for queries about Refunds.
</Info>

<Info>
  **Example**: you may discover that your model's average response time is 1.3s
  for queries about Shipping, but 5.4s for queries about Product Availability.
</Info>