> For the complete documentation index, see [llms.txt](https://docs.intelligems.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.intelligems.io/integrations/analytics-and-data-platforms/heatmap-integrations/integrating-with-microsoft-clarity.md). # Microsoft Clarity ## Introduction The Intelligems Microsoft Clarity integration tags visitor sessions with experiment data, allowing you to analyze behavior patterns across different test groups. ## **How It Works** Enable the Microsoft Clarity integration on the Integrations page in Intelligems. {% hint style="info" %} Note that when you set up the Microsoft Clarity integration, you will not need to enter any login information - we use Microsoft Clarity's window API to authenticate. {% endhint %} Once active, Microsoft Clarity sessions will include events tagged with test group information following this pattern: \ - \ allowing you to view/filter sessions in Clarity by experiment name and test group name. You can filter by `experiment_name` or `ig_test_group` under the custom tags as seen below:
## **Benefits** Filter and compare sessions in Clarity by experiment to understand how different variations affect user behavior. See which test groups have higher engagement, where visitors drop off, or how different audiences interact with your site. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.intelligems.io/integrations/analytics-and-data-platforms/heatmap-integrations/integrating-with-microsoft-clarity.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.