Prospecting Data Sources

Tool selection guide for prospecting across all three branches.

Tool selection by goal

Goal	Primary tools	Notes
Build initial firmographic list (B2B / SaaS)	Apollo, ZoomInfo, Clay	Apollo for breadth, ZoomInfo for enterprise + intent, Clay for custom workflows
Decision-maker mapping	LinkedIn Sales Navigator (manual), Apollo, ZoomInfo	Sales Nav is the gold standard. Never bulk scrape it.
Tech stack qualification (SaaS)	BuiltWith, Wappalyzer	BuiltWith has wider coverage + paid plans for bulk; Wappalyzer is lighter + free for small use
Funding signals (SaaS)	Crunchbase, Pitchbook	Crunchbase free tier sufficient for early signals; Pitchbook for deeper investor data
Email pattern discovery	Hunter, Snov, Apollo	Pattern guessing — followed by verification
Email deliverability verification	Truelist, Hunter, NeverBounce, ZeroBounce	Always verify before adding to outreach lists
Visitor identification (warm intent)	RB2B, Clearbit Reveal	Anonymous traffic → company identification
Intent data	ZoomInfo Intent, 6sense, Bombora	Pre-warmed signals; mid-market+ pricing
Trigger event monitoring	Google Alerts, Feedly, LinkedIn Sales Nav alerts	Free options are sufficient for most
Local business discovery	Google Maps (manual), Yelp, Facebook Pages	Browser-assisted, not bulk-extracted

Apollo

Use for: General B2B / SaaS firmographic + contact data. Best starting point if you don’t already have a list.

Strengths:

Large database (>200M contacts, >60M companies)
Strong filtering UI (industry, size, technologies, signals)
Integrated email + LinkedIn finder
Pay-as-you-go and tiered plans

Watch out for:

Data freshness varies — re-verify before scoring as “Hot”
Email accuracy ~60–80% — always validate
Bulk export limits apply

Integration: see apollo.md

Clay

Use for: Multi-source enrichment, waterfall lookups, custom scoring logic. When list quality matters more than list size.

Strengths:

Waterfall logic: try Apollo first → fallback to ZoomInfo → fallback to Clearbit
100+ data provider integrations
AI-powered enrichment (LLM-driven extraction from URLs)
Custom columns + scoring formulas
Native MCP server

Watch out for:

Per-credit pricing can spike on large lists
Complexity overhead — easy to over-engineer workflows

Integration: see clay.md

ZoomInfo

Use for: Enterprise B2B + intent data. Mid-market+ buyer profiles.

Strengths:

Enterprise-grade firmographic depth
Intent signals (companies searching topics relevant to your offer)
Best-in-class for >$50K ACV B2B sales
Native MCP server

Watch out for:

Expensive ($15K+/yr starter)
Overkill for SMB prospecting
Locked into multi-year contracts typically

Integration: see zoominfo.md

Clearbit

Use for: Email → company enrichment, anonymous visitor identification (Clearbit Reveal).

Strengths:

Strong company enrichment (industry, size, funding, tech stack)
Email lookup by domain
Reveal: identify anonymous site visitors at company level
API-first

Watch out for:

HubSpot acquisition (2023) — bundled into HubSpot Breeze Intelligence now
Standalone API still available but pricing/access depends on tier

Integration: see clearbit.md

Hunter / Snov

Use for: Email pattern discovery + lightweight verification on small lists.

Hunter strengths:

Domain-based email discovery
Built-in deliverability verification
Free tier reasonable for occasional use

Snov strengths:

Email finder + drip campaigns (overlap with outreach tooling)
Bulk verification
Cheaper than Hunter at scale

Watch out for:

Both are pattern-guessing tools — accuracy depends on the target company’s email pattern being inferable
Always run results through a dedicated validator (Truelist or similar) before outreach

Integrations: see hunter.md, snov.md

Truelist

Use for: Email deliverability validation before adding contacts to outreach lists. Critical safety step.

Strengths:

Single-email sync verification (/api/v1/verify_inline) + bulk async (/api/v1/verify)
Returns email_state (ok / email_invalid / risky / unknown / accept_all) + email_sub_state (email_ok / is_disposable / is_role / unknown_error / failed_smtp_check) + did-you-mean typo suggestions
Catches catch-all domains, role accounts, spam traps, disposable providers
Official MCP server for agent-driven workflows (Claude, Cursor, VS Code)
Official SDKs in 7 languages + framework integrations (Django, Laravel, Next.js, Rails, React, Svelte, Vue, WordPress)
Native integrations with Mailchimp, Klaviyo, HubSpot, Zapier, Make, n8n, Clay, Salesforce, more
Pay-per-email pricing

Why this matters: Cold email reputation craters when bounce rates exceed 2%. Validating before sending is non-negotiable. Apollo/ZoomInfo/Hunter data is often 60–80% accurate — Truelist catches the rest.

Integration: see truelist.md

LinkedIn Sales Navigator

Use for: Manual decision-maker discovery. The gold standard for B2B / SaaS prospecting but only when used as a research tool.

Strengths:

Most accurate decision-maker data in the industry
Real-time job changes, posts, signals
Lead lists, alerts, saved searches
Inmail credits (separate channel from cold email)

Hard rules:

Never bulk scrape. LinkedIn aggressively bans scrapers. Account ban risk is real and permanent.
Use Sales Nav as a research interface — open profiles, read, take notes, capture key data manually.
Apollo and other tools claim LinkedIn data via partnerships / public mirroring — verify the source legitimacy before assuming compliance.

Integration: no MCP or API access at consumer level. Manual research only.

BuiltWith / Wappalyzer

Use for: Tech stack qualification (SaaS branch).

BuiltWith:

~50K+ technologies tracked
API + bulk lookups (paid)
Historical data (when stack changed)

Wappalyzer:

Free browser extension; paid API
Lighter coverage than BuiltWith
Faster for one-off lookups

Cross-reference both for high-confidence tech stack signals.

Crunchbase

Use for: Funding signals (SaaS branch).

Strengths:

Free tier shows recent funding events
Paid (Pro / Enterprise) unlocks alerts and deep history
API access for paid users

Watch out for:

Coverage is best for VC-backed companies; bootstrapped + small businesses underrepresented
Self-reported data — verify funding amounts independently

GitHub (stargazers / forks / watchers)

Use for: Developer-intent prospecting. Especially powerful for dev-tool SaaS — stargazers of competitor or category-defining repos are in-market signal.

Strengths:

Public API, no scraping concerns
High signal quality (a starred repo = explicit interest)
Forks are an even stronger signal (intent to modify, not just bookmark)
Bundled github-prospects.js CLI handles pagination + enrichment + CSV output
Free with 5,000 req/hr authenticated rate limit

Watch out for:

Only ~5–20% of users publish email — pair with Apollo/Clay/Hunter for enrichment
Very-popular repos (100K+ stars) are mostly noise; smaller targeted repos (5K–25K) give better signal density
Most prospects are individuals, not company contacts directly — need to figure out their company from company field or LinkedIn

Integration: see github.md

Firecrawl / Browserbase (single-target site research)

Use for: Programmatically extracting content from a prospect’s own website that you already found via discovery on platforms like Google Maps, Yelp, or LinkedIn. Not for scraping those platforms themselves.

Firecrawl

Best for: “Just give me the page as markdown” — Local SMB website status checks, B2B company about/team page extraction, structured field extraction
Strengths: Low overhead, returns clean LLM-ready markdown, handles most JS-rendered sites, has an MCP server
API + MCP + SDKs: Node, Python, Go, Rust

Browserbase

Best for: When you need real Chromium — JS-heavy pages, cookie consent dialogs, form submission to reach a contact page, session state
Strengths: Full browser control via Playwright/Puppeteer; Stagehand provides AI-friendly natural-language extraction; session recordings for debugging
API + MCP (Stagehand) + SDKs: Node, Python

Critical compliance line

Both tools can technically point at any URL. The hard rule:

✓ OK: extracting content from a single business’s own website (joescoffeeshop.com) that you found through manual discovery
✗ NOT OK: pointing them at google.com/maps, LinkedIn search results, Yelp listings, or any platform whose ToS prohibits bulk extraction

Discovery happens on platforms (manual browser-assisted research). Extraction happens on individual public business sites.

Integrations: see firecrawl.md, browserbase.md

RB2B / Clearbit Reveal

Use for: Identifying anonymous site visitors as warm intent signals.

Strengths:

Pixel-based visitor → company identification
High-intent: they came to your site, they’re already in research mode
Slack / email alerts on key visits

Watch out for:

Privacy/GDPR considerations — verify your privacy policy disclosures
Person-level identification raises higher concerns than company-level

Integration: see rb2b.md

Free / browser-only fallbacks

When the user has no paid tools, lean on:

Google Search — exact business name + city + role searches
LinkedIn (manual, no scraping) — company pages, employee lookups
Crunchbase free tier — funding events
Wappalyzer browser extension — tech stack at a glance
Hunter.io free tier — 25 lookups/month
Google Maps — for Local SMB discovery
Business websites + About pages — primary source for any claim
News sites + press releases — trigger event monitoring via Google Alerts

Slower than tooled-up workflows, but produces high-quality smaller lists if the user is willing to do the work.

Sequencing recommendations

A typical full-stack prospecting workflow:

Define ICP from product-marketing context (no tools needed)
Initial list from Apollo or ZoomInfo (firmographic filter)
Enrich with Clay (waterfall: tech stack, funding, trigger events)
Decision-maker mapping in LinkedIn Sales Nav (manual)
Email pattern discovery with Hunter or Apollo’s built-in
Email validation with Truelist before final list
Hand off to cold-email skill for outreach copy

Adapt this sequence based on which tools the user actually has.