{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/b1360fc9bde44cc9adb56040ce297352\" frameborder=\"0\" width=\"3442\" height=\"2581\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":2581,"width":3442,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":2581,"thumbnail_width":3442,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/b1360fc9bde44cc9adb56040ce297352-0b86efb1c5c6adde.gif","duration":759.367,"title":"Workflows Enrichment, Build Creative Data Juice","description":"This Loom explains how to enrich workflows in Clay using the FET framework updated to T-E-A. It describes replacing FIND with T for dynamic targeting, combining Enrich and Transform into a single command for enrichment, and using Act instead of Export to action data natively, with an emphasis on future self learning revenue systems coming in 2027. The presenter outlines a PE partnership enrichment strategy: enrich companies and people with demographic and firmographic data, filter portfolio companies headquartered in the US, calculate industry percentage breakdowns with an over 15 percent threshold, check for existing Clay customers, and gather GTM relevant news and GTM optimization experience. They run tests on 2,851 firms, note issues like only counting the first page of results and incorrect industry labeling, then suggest switching to stronger models such as Opus 5.5 to improve exhaustiveness and address model quality before continuing to the act step."}