> For the complete documentation index, see [llms.txt](https://docs.hockeystack.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.hockeystack.com/integrations/ad-platforms/linkedin-ad-impressions-and-engagement/linkedin-company-intelligence.md). # LinkedIn Company Intelligence HockeyStack's integration with LinkedIn's Company Intelligence enables you to view company-level engagement data paired with revenue outcomes. You'll gain daily insights and detailed metrics on how companies engage with both organic and paid LinkedIn activity. ### What does this integration do? This integration collects engagement data from LinkedIn’s Company Intelligence API and gives you a clear view of: * Paid Impressions * Paid Clicks * Paid Engagements * Organic Impressions * Organic Engagements Additionally, it supports data for up to 100,000 companies, significantly more than the Reporting API's 5,000-company limit. ### How are daily numbers calculated? LinkedIn shares engagement data as a **rolling 7-day total** for each company. Our system uses a proven method to estimate the number for each individual day, so you don’t miss out on trends and changes. **Important Note:**\ Because LinkedIn’s API does not support day-by-day data—our daily estimates use a combination of historical values and known totals. This means the numbers **may not be 100% precise** for each day, but they are designed to be as close as possible over time. ### When is data updated? * We collect new data every day * LinkedIn updates reporting with a **2-day delay** ### Why do numbers differ from LinkedIn sometimes? Because the API provides summary statistics in 7-day windows (not exact daily counts), our integration estimates daily numbers using a best-practice method. This approach helps uncover real trends, even if the exact count for one day isn’t available.\ \ You can find official LinkedIn API documentation [here](https://learn.microsoft.com/en-us/linkedin/marketing/account-intel/account-intel-api?view=li-lms-2025-10\&tabs=http) --- # 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.hockeystack.com/integrations/ad-platforms/linkedin-ad-impressions-and-engagement/linkedin-company-intelligence.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.