{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/362f8c13234649699395e632652cb192\" frameborder=\"0\" width=\"1126\" height=\"844\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":844,"width":1126,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":844,"thumbnail_width":1126,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/362f8c13234649699395e632652cb192-8c3dc90e0051ef26.gif","duration":560.5,"title":"How to Improve Match Rate","description":"This Loom explains how to improve enhanced matching by filling gaps in your data, then how to correctly interpret match rates after a sync. It emphasizes the highest leverage step of filling missing LinkedIn URL fields in your target segment using bulk enrich, with the enrichment configured to run only when LinkedIn URL is empty and to preview on 10 rows before running the remaining 444 rows, at an estimated 2.9 credits per row. When reviewing results, it cautions that platforms use different denominators, so you should check hashed email coverage first since match counts and match rates can vary across LinkedIn, Meta, and Google. It also notes that platforms do not show which specific context matched, so debugging should focus on the full list and segment-level variation, with typical provider errors strongest in North America."}