Troubleshooting Inaccurate Employee Counts from Waterfall Logic

Hi Support - I'm running an enrichment to pull employee counts for companies and I'm seeing quite a few cases where the data from the waterfall logic doesn't look very accurate. For example:

https://www.linkedin.com/company/-tesco/ -> Clay is pulling an employee count of 2
https://www.linkedin.com/company/dick%27s-sporting-goods/ -> getting an employee count of 3
https://www.linkedin.com/company/gotogroup/ -> getting an employee count of 2

Any idea of how to troubleshoot this?

4 comments

Channeled
APP
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To improve the accuracy of employee count data in your enrichments, try adjusting these settings: 1. Increase the "Minimum Likelihood Score" parameter - For high data accuracy, use a score of 6 or higher. 2. Provide multiple company identifiers when possible: • Company domain • LinkedIn company profile URL • Company stock ticker • Company name 3. When using People Data Labs for employee counts, ensure you've specified at least one of these required filters: • Role Filter • Country FilterThese adjustments should help improve the quality of the employee count data you receive through the enrichment process. Sources: Enrich Company with People Data Labs Get Employee Count by Criteria with People Data Labs
Sameera P.
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Where can I find the Minimum Likelihood Score" parameter?
Channeled
APP
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The "Minimum Likelihood Score" parameter is an input field available in People Data Labs enrichment operations. You can find it in the input settings when using either: • "Enrich Company with People Data Labs"• "Get Employee Count by Criteria with People Data Labs"This parameter helps control the accuracy of your data - a score of 6 or higher is recommended for high data accuracy (this is the default setting). Sources: Enrich Company with People Data Labs Get Employee Count by Criteria with People Data Labs
Channeled
APP
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