How To Use Apollo.io 2026 - Full Tutorial

Product reviewed

Apollo.io — used for outbound lead generation, sequencing, calling, and sales tracking.

Key features mentioned

All-in-one outbound workflow

Apollo combines:

• Searching/finding contacts & accounts
• Scoring leads
• Running outbound email sequences
• Calling
• Tracking meetings, deals, and analytics in one platform

Prospecting database + list building

Apollo includes extensive filtering for building targeted lead lists, including:

• Name, email status
• Job title
• Company
• Location (including HQ vs. contact location)
• ZIP/radius
• Employee headcount
• Industry, keywords
• Buying intent (mentioned, but the speaker doesn’t personally use it)
• SIC codes / technologies
• Revenue, funding
• Job postings, territories, lead stages, and more

Additional workflow details:

• Shows lead counts and allows saving leads into lists.
• Example process: build a granular search (e.g., “managed IT” companies) → generate ~500 leads → add to a list.

Email sequencing inside Apollo

• Build sequences and connect email accounts
• Run sequences and view call/email analytics
• AI-assisted sequence building is mentioned

Exports for use in other tools

• Export lead lists to CSV / Google Sheets-style workflows
• Exports can use CSV export settings with optional fields

Enrichment/validation workflow (primarily via third parties)

• Apollo provides an email status (e.g., verified/guessed), but the speaker still recommends third-party validation to reduce bounces.
• Suggested validation tools:
  • MillionVerifier
  • Listman
• Enrichment workflows mentioned:
  • Clay (AI checks/summarization, enrichment, and data cleanup)

Calling / engagement

• Apollo includes dialing and engagement tracking (no deep tutorial details provided in the subtitles).

Company-level targeting

• Use the “Companies” tab to filter accounts
• Transfer criteria from “People” to “Companies” to create tighter account lists
• Strategy described: “guessing and checking” using keywords and seed ideal companies to broaden then narrow

Pricing / numerical info

• Free plan available
• Free plan includes 10 export credits/month and some basic features
• Scaling uses a credit-based system for more exports/leads

Data quality, accuracy, and limits (pros/cons)

Pros

• High perceived data quality, largely attributed to sourcing from LinkedIn (where people self-report job title/company info).
• Speaker uses Apollo for millions of emails sent and claims it helped book 2,000+ sales meetings for customers (speaker’s experience).
• Filters help refine results, including:
  • Job titles
  • Exact-match searches using quotes
  • Exclusion filters (e.g., avoiding “VP” / “Vice President”)
• Apollo-derived lead lists are exportable and workable in other systems (e.g., Clay/CRM/email sequencers).

Cons / cautions

• “Verified” emails are not real-time verified—verified is historical/at some point.
• Speaker estimates ~5–10% of Apollo-pulled emails may be invalid, so third-party validation is needed to avoid bounces.
• Revenue estimates aren’t reliable for private companies (unless public companies).
• Buying intent isn’t used by the speaker; peer experience suggests similar results without it, and it can add cost.
• Some niches may be underrepresented on LinkedIn (e.g., blue-collar/contractors like plumbers/electricians), reducing completeness of employee/headcount filters.

Mobile direct dial detail

• Apollo “direct” phone fields may cost extra; mobile phone can be a separate charge (at least for that field).

User experience (workflow described)

1. Use Apollo to search/build lists using advanced filters.
2. Save leads and optionally run Apollo sequences.
3. Per the speaker, it’s best to export for:
   • Email validation (MillionVerifier / Listman)
   • Enrichment/workflows (Clay)
   • Importing into email/lead ops tools (mentioned generally: Clay, smartlead, etc.)
4. After validation/enrichment, run sequences/campaigns.

Comparisons / integrations mentioned

Apollo vs. specialized tools

• The speaker prefers other tools for sequencing/calling:
  • Smartly (email sequencing)
  • Close (power dialers/CRM tracking)
• For validation:
  • Listman / MillionVerifier
• For enrichment:
  • Clay (“Google Sheets on steroids” for AI workflows and data cleaning)

CRM / tracking examples

• HubSpot
• Close (used for tracking meetings/deals as part of the broader workflow)

Unique points mentioned (consolidated list)

1. Apollo is positioned as an all-in-one outbound platform (search, score, email, calling, meeting/deal tracking, analytics).
2. Speaker has used Apollo for ~2+ years, scraping hundreds of thousands of leads and booking 2,000+ sales meetings for customers.
3. Free plan exists; upgrades are credit-based for more exports/leads.
4. Apollo excels as a database/list-building tool for prospecting.
5. List building supports many filters: email status, job titles, company, location (HQ/contact), ZIP/radius, employee headcount, industry/keywords, SIC/technologies, funding, job postings, etc.
6. LinkedIn is described as the primary data source; self-reported info improves accuracy.
7. Speaker cites ~220 million total leads as shown in the interface.
8. Speaker saved 600,000+ leads and had ~219 million unsaved (interface display).
9. Email status nuance: verified vs guessed, and “verified” is not real-time.
10. Recommendation: validate emails externally; speaker estimates 5–10% may be invalid.
11. Job title searches can handle synonyms (e.g., CEO vs Chief Executive Officer) and exact match with quotes.
12. Exclusion filters can use partial terms (e.g., VP/Vice President).
13. Company search by domain (e.g., apple.com) can introduce noise.
14. Export-based workflows: select leads → save/export → CSV for other tools.
15. Example managed IT search produced ~500 people, shown as 491 in their saved/exported list.
16. “Companies” tab supports targeted account lists; criteria can be transferred from people-level to company-level.
17. List-building is iterative: seed ideal companies → use keywords → broaden/narrow via guessing and checking.
18. Apollo exports can include many fields (phones, seniority, technologies, etc.), but the speaker filters columns to avoid clutter.
19. Mobile phone may require extra payment.
20. Clay is used for AI enrichment/verification (e.g., checking whether a company is managed IT).
21. Apollo data can be validated via tools like MillionVerifier/Listman before campaigns.
22. Speaker doesn’t rely on revenue or buying intent features (revenue inaccurate for private companies; buying intent costs extra without value, per the speaker).
23. Revenue filter is considered unreliable due to private company estimates.
24. Revenue/buying intent exist, but the speaker prefers intent/fit from other observable signals.

Pros mentioned (summary)

• Strong data coverage and search/list-building features
• High perceived data quality from LinkedIn sourcing
• Flexible exports enabling prep across multi-tool stacks
• End-to-end outreach possible from one platform (though the speaker mainly uses Apollo for data)

Cons mentioned (summary)

• Email verification is not real-time; expect ~5–10% invalid emails → validate externally
• Revenue estimates unreliable for private companies
• Buying intent feature not worth it (cost/benefit)
• Some niches may be less accurate due to LinkedIn presence (blue-collar/contractors)

Overall verdict / recommendation

Recommended primarily as a lead database and list-building engine (search/prospecting + export), with a clear warning that you should always run email validation externally.

Use Apollo to build targeted lists, then integrate with:

• Email validation (Listman / MillionVerifier)
• Enrichment workflows (Clay)

This approach is positioned as the best way to improve campaign results.