Brian T. Clay can’t scrape LinkedIn connections directly. Best practice is enrich with Clay for company/people data, then use a LinkedIn tool like LinkedHelper, Phantombuster, or Sales Navigator to map mutual connections. Combine both and you’ll know where warm intros exist
Find People filter by department/title (like IT, HR, etc.) and then count them with a rollup/aggregate column. That’ll give you department-wise headcount
in that case better to pre-filter in Supabase with SQL, then send only the reduced set into Clay as context. Pulling everything raw into the LLM will always be costly
Alexander F. no native Supabase MCP in Clay. Either host your own MCP (Vercel/GCP) or just hit Supabase REST/PostgREST API in Clay to pull only needed rows
Joshua P. few things you can tweak: 1) Try more signals than just open jobs (funding, team growth, tech stack shifts). 2) Hiring managers are fine but test CXOs too for better replies. 3) Bounce rate likely from email enrichment flow run a single verify at the end instead of every step. 4) Scripts may need personalization beyond job openings. These usually lift reply rates
there isn’t really an API that flags “free to InMail” profiles directly. Best workaround is using LinkedIn’s own Sales Nav filters or enrichment tools like Clay + Apollo to check messaging options
Yes, that’s it PredictLeads only works with the Company Domain. If you map both Domain and LinkedIn URL, it runs twice per row, which doubles credit usage. Just use the Domain to avoid this
