Find Decision Makers and Contact Information from Company Names back to library

~ / library / Prospecting / find-decision-makers-and-contact-information-from-company-names

Find Decision Makers and Contact Information from Company Names

Finds senior decision-makers (Director, VP, Head, C Suite, Owner, Partner) and their emails for a list of companies using MoltSets. Works for any CSV of company names + domains, not just exhibitor lists. Handles messy real-world data like name collisions, missing domains, and emails that aren't indexed under the obvious search.

// example prompts

find people at these companies
get me contacts for this exhibitor list
senior execs at each of these companies

// about this skill

What this skill does

Turns a raw list of companies (name + domain, typically from an event exhibitor list) into a table of senior contacts with verified email addresses. Built from hard-won trial and error against messy small-business data — most companies on a list like this are NOT well-indexed, and the naive approach (search_people with a company_domain filter, stop after 2 hits) misses the majority of real, findable emails.

Chain

CSV of company name + domain
  to search_people            (free-text query first, then exact company name for the fuller roster)
  to linkedin_to_best_email / search_business_email_by_name   (chase an email per qualifying person)
  to reverse_linkedin_lookup  (confirm an email genuinely doesn't exist)
  to reverse_email_lookup     (pattern-guess common conventions, batched)

Inputs

Company list — name + domain per row (exhibitor list, prospect list, account list)
Target seniorities — default: Director, VP, Head, C Suite, Owner, Partner
Emails per company — asked up front, never silently defaulted
LinkedIn-only fallback — whether to fill the count with LinkedIn-only rows when email comes up short

When it activates

"find people at these companies"
"get me contacts for this exhibitor list"
"senior execs at each of these companies"
A CSV with company name/website columns uploaded alongside a request for contacts

Output

A CSV: row, company, domain, contact_name, title, seniority, email, email_type, verification_status, linkedin_url, notes. Every match is tagged VERIFIED / INFERRED / UNVERIFIED / NOT FOUND so rows are safe to act on — LinkedIn-only fills and stale addresses are flagged, not silently mixed in.

Tips

Free-text query beats the exact company and company_domain filters on messy small-business data — start there, then use the exact stored name to pull the fuller roster
Chase order per person: email in the search result → linkedin_to_best_email → search_business_email_by_name → reverse_linkedin_lookup → pattern-guessing
Pattern-guess a standard 6-convention set through reverse_email_lookup (batched, up to 100 per call, no token cost on misses) before giving up — it finds real emails the forward tools miss
Calibrate on a ~20-row batch first; expect roughly half to two-thirds of small/local exhibitors to yield usable contacts