Fill the gaps: email, phone, LinkedIn, title.

“I have a list of names and companies and I am missing every email and phone.”

Give it a name and company, or a domain, and get contacts or firmographics back. Waterfalls across your tools.

FIND MORE PIPELINEADVANCEDENRICHMENT TOOLSSEQUENCERCRM✓ APPROVED 4/4
EXAMPLE PROMPTS
>Enrich this CSV with emails, phones, and LinkedIn URLs [pastes list]
>Who are the decision makers at [company]?
>Get headcount, funding, and tech stack for these domains and fill the gaps
ABOUT THIS SKILL

What this skill does

This is your data-fill agent. Give it a name and a company, and it finds the email, phone, LinkedIn URL, and title. Give it a domain, and it returns headcount, funding, a technographic profile, and hiring intent. It works one contact at a time or across a whole list, tries the cheapest provider first, and tags every value it returns with how confident it is. It never invents a value it could not find.

Inputs

  • Works today with: your list of names and companies, or domains. Paste or upload a CSV. The skill structures it, flags what is missing, and tells you exactly which source would fill each field.
  • More powerful connected to a contact-enrichment tool: emails, phones, LinkedIn URLs, and titles, run as a waterfall.
  • More powerful connected to a company-enrichment tool: headcount, funding, hiring signals, and technographic profile. Either source alone works at reduced coverage; both run the full waterfall.
  • Sharper with a people-search tool (LinkedIn identity validation) and a CRM (read records in, write enriched values back).

How it works

  1. 1
    The core pattern is a cost-aware waterfall. For any field, try providers in order, cheapest first, and stop the moment you get a confident answer.
    1. Read the input. For each row you need a name plus a company (contact mode) or a domain (company mode). Note fields already present so they are not re-bought.
    2. Run the contact waterfall. For email, phone, LinkedIn, and title, try providers in order. Take the first confident hit. Tag each field with its confidence.
    3. Run the company pass. For a domain, return headcount, funding, hiring signals, and the technographic profile.
    4. Discover the buying committee. For a "who are the decision makers" request, return the senior roles per account, each with confidence-tagged identifiers.
    5. Validate every LinkedIn URL. Cross-check the name and company on the profile against the input. If they do not match, do not return the URL.
    6. Track spend. Log credits per provider. If the run hits the cap, stop and return partial results with a note.
    7. Return confidence-tagged rows plus an audit of providers used, the confidence breakdown, and total cost.

Output format

Enrichment Complete  ·  5 contacts processed

Name       | Email                     | Phone        | Title
-----------|---------------------------|--------------|-------------------
Contact A  | a@example.co (verified_2) | +1-555-0101  | VP Sales (verified)
Contact B  | b@example.co (verified_1) | not_found    | CRO (inferred)
Contact C  | c@example.co (verified_2) | +1-555-0102  | CFO (verified)
Contact E  | not_found                 | not_found    | not_found

Audit:
  Confidence breakdown: 8 verified_2, 4 verified_1, 1 inferred, 3 not_found
  Total cost: within run cap
  Skip Contact E: source the LinkedIn URL manually before reaching out.

Tips

  • Confidence-tagged outputs. Every enriched field comes back with its source confidence, never a bare value.
  • Identity validation on LinkedIn URLs before they ship. This blocks returning the wrong person.
  • Cost-aware waterfall. The cheapest provider is tried first. Per-provider credit use is logged.
  • Honest "not found." If a value cannot be found, return null plus not_found rather than guessing.
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