> For the complete documentation index, see [llms.txt](https://docs.makerobos.com/chatman-enterprise-whatsapp-platform/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.makerobos.com/chatman-enterprise-whatsapp-platform/chatman-functions/instinct-ai/summary.md).

# Summary

Here, you will obtain a deep understanding of the intents asked, helping you know the interests and problems that visitors/customers face with your business, and accordingly, you can draft a specific message or journey for the same.

<figure><img src="/files/uv1ugirWqoktq0Ea7q8X" alt=""><figcaption></figcaption></figure>

### Key Points  In Summary

#### Intent

Intents are the names/queries that you want the bot to understand. Under intent, you can see a list of intent names and, besides that, their performance. Knowing the accuracy and effectiveness of intents is crucial for assessing the bot's overall performance.&#x20;

#### Messages

Messages tell you about the frequency, i.e., how many times a particular intent has been sent by a bot. Knowing the frequency, tells about regular intents, and you can train the bot accordingly to respond back with a better reply.

#### Importance

Assigning appropriate importance levels to intents ensures that the bot prioritizes and handles critical tasks effectively.&#x20;

#### Accuracy

High intent accuracy is a key indicator of a well-trained bot. Regularly assessing and improving accuracy helps in refining the bot's natural language understanding, reducing errors, and enhancing the overall user experience.&#x20;

#### Catch-All

Analyzing the catch-all performance aware of how effective the catch-all mechanism is and hence tells about user interactions. It helps to know the situations where the bot might not have a specific intent defined for a particular user input.