Apollo Search

Apollo Search

Search Apollo's 210M+ contacts and 35M+ companies to build targeted lists, then enrich them — through ColdIQ's resold Apollo endpoints /v1/apollo/* (same Apollo filter semantics, one ColdIQ key). Use Apollo to BUILD the list (search + filter); use coldiq-search-enrich to ENRICH it with emails.

ColdIQ Marketplace Endpoints

Standard Workflow: Search Then Enrich

1. Search people with filters (returns IDs + basic info, not emails). → POST /v1/apollo/people/search · 1 cr · apollo.people.search

   { "person_titles": ["VP Sales", "Head of Growth"], "person_seniorities": ["vp", "director"],
     "organization_num_employees_ranges": ["51,200"], "per_page": 100, "page": 1 }
   

2. Collect IDs from the results.
3. Bulk enrich in groups of 10 (never one-by-one). → POST /v1/apollo/people/bulk-match · 1/person · apollo.people.bulk_match
4. You now have emails, phones, LinkedIn URLs, and employment history.

For full company firmographics use single-org enrich, not bulk: → POST /v1/apollo/organizations/enrich · 1 cr · apollo.organizations.enrich

Top Filters

Company: organization_num_employees_ranges, revenue range, q_organization_keyword_tags (industry/keywords), organization_locations, funding stage, technologies, job postings, year founded, department headcount, buying intent (Org plan only).

People: person_titles, person_seniorities (c-suite, vp, director), department, person_locations, include_similar_titles, recent job change, time in role, has email/phone, contact_email_status.

Employee count ranges (API values)

"1,10"  "11,50"  "51,200"  "201,500"  "501,1000"  "1001,5000"  "5001,10000"  "10001,50000"

Proven Search Configurations (examples)

• Referral-ceiling founders: 10–200 emp, $1–10M rev, software/internet, Seed/Series A, US/UK/W-Europe, sales dept 0–2 → titles Founder/CEO/Owner.
• Failed DIY outbound: 10–100 emp, uses Apollo/Lemlist/Instantly/Outreach/SalesLoft, sales dept 1–5 → VP Sales / Head of Growth / Founder.
• Enterprise B2C: 501+ emp, $100M+ rev, financial/automotive/retail/insurance/pharma, US → CMO / VP Growth / Head of Brand / Head of SEO.

Filter Building

Start broad (industry + size + location) → check count (target 500–5,000) → add keywords → add signals (tech/intent/job postings) → add people filters last. Too few (<500)? loosen size. Too many (>10,000)? add funding stage or department headcount.

Gotchas

1. Industry is self-reported — "Information Technology & Services" is a catch-all.
2. Revenue is estimated — unreliable for private companies under $10M.
3. Technologies = website tracking only — internal tools (Slack, Notion) won't appear.
4. Employee count lags 3–6 months for fast-growing startups.
5. Bulk org enrich returns stripped data — missing latest_funding_stage, total_funding, annual_revenue, technology_names[]. Use single-org enrich for full firmographics.
6. Search never returns emails — enrich after search.
7. Buying intent requires the Organization plan.

Apollo vs ai-ark vs Exa