LinkedIn Decision-Maker Finder
Pricing
Pay per usage
Find the right LinkedIn decision-makers from names, company pages, people-search URLs, or exact profile URLs, then return confidence-scored matches with optional public profile and contact enrichment.
Pricing
Pay per usage
Rating
0.0
(0)
Developer
Netdesignr
Actor stats
1
Bookmarked
33
Total users
22
Monthly active users
7 days ago
Last modified
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Choose whether to stop at matching, enrich matched profiles, or enrich matched profiles plus public contact data. Match billing applies only to successful matches. Contact billing applies only when contact data is returned.
Optional hint for how you are supplying data. The actor can also auto-detect mixed input.
Free-text or Boolean-style people-search queries. One query per line. Good for broad discovery like founder fintech london or vp sales saas germany.
Structured rows for CSV-like enrichment workflows. Recommended columns: id, name, company, title, location. This is the best option for CRM or Clay enrichment jobs.
Public LinkedIn people-search URLs to convert into no-cookie discovery queries. Use this when you already have a LinkedIn people search and want export-ready matches.
Company LinkedIn URLs used to discover likely decision-makers from public search results. Best for founder, CEO, VP, or director discovery per account.
Exact public LinkedIn profile URLs. This is the most deterministic input style and is recommended for large-scale re-processing or known-profile enrichment workflows.
Maximum matched outputs to produce across the run. This is a hard cap on returned matches.
Only return candidates at or above this score from 1-100. Raise this when you want fewer but safer matches.
Remove duplicate LinkedIn profile URLs inside each input row's candidate set.
Optional location text used in query building and confidence scoring.
Optional seniority hint such as executive, director, or manager.
Optional top-level company hint applied when row-level company is missing.
Optional title keywords used for company discovery and confidence scoring.
Optional company size hint kept for downstream workflow context.
Attempt to normalize public experience history when available.
Attempt to normalize public education history when available.
Attempt to normalize visible public skills when available.
When enabled, look for public email and phone data on the company website. Contact enrichment is best effort and only billable when contact data is returned.
