SaaS Prospecting Reference

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Generated from core/skills/prospecting/references/saas-prospecting.md — edit that file, not this page.

SaaS Prospecting Reference

For when the user sells SaaS or digital services to other SaaS companies / digital businesses.

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ICP Signals That Matter (SaaS branch)

Beyond standard firmographics (industry, size, geography), SaaS prospects are qualified by:

Technographic signals

• Tech stack — do they use complementary tools (your integration target) or competing tools (a switch opportunity)?
• Recent stack changes — adding/removing tools signals active vendor evaluation
• Custom-built vs off-the-shelf — DIY tooling often means a buyer who’d benefit from your product
• Free/freemium plan signals — using a free competitor means they may be ready to upgrade

Growth signals

• Funding round — Series A / B / C in last 6 months = budget + new hires + tool needs
• Headcount growth — 10%+ growth in last quarter signals scaling pressure
• Hiring signals — specific role openings (e.g., “Head of RevOps” → ICP for revops tooling)
• Product velocity — frequent shipping, new features, blog posts = healthy growth motion
• Open positions for your buyer’s role — if you sell to Marketing Ops and they’re hiring one, that’s a signal

Decay signals (downgrade scoring)

• Layoffs in target department
• Funding round >2 years ago with no follow-up
• Product hasn’t shipped in 6+ months
• Team page shows founders only (very early — may not have budget)

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Discovery Sources (SaaS branch)

Combine 2+ sources for cross-verification.

Tier 1 — primary discovery

• Apollo: firmographic + technographic + contact data. Good for building large initial lists.
• Clay: waterfall enrichment, custom scoring, multi-source merges. Best for high-quality smaller lists.
• ZoomInfo: enterprise-grade firmographic + intent signals. Expensive; mid-market+.
• LinkedIn Sales Navigator: decision-maker mapping. Use manually, never bulk scrape.

Tier 2 — technographic / growth signals

• BuiltWith: tech stack lookups, find sites using specific tools
• Wappalyzer: free browser extension + API; lighter tech stack signal
• Crunchbase: funding rounds, headcount, founders
• Pitchbook: deeper investor data (enterprise/paid)
• ProductHunt: recent launches, builder audience
• Hacker News / Show HN: technical builders launching products

Tier 3 — buying signals

• Job boards (LinkedIn Jobs, Indeed, AngelList): role openings as signals
• RB2B / Clearbit Reveal: visitor identification (warm anonymous traffic)
• GitHub stars/forks of competitor or adjacent repos: developer-level intent signal (see tools/integrations/github.md and the github-prospects.js CLI). Especially strong for dev-tool SaaS — a developer who starred vercel/next.js last week is in-market for adjacent Next.js infrastructure.
• Recent blog posts / changelog: product direction signals
• G2 reviews mentioning competitor switches: explicit dissatisfaction signal

GitHub prospecting pattern (when audience is developers)

For dev-tool SaaS, GitHub is one of the highest-quality discovery channels:

1. Identify 3–5 “anchor” repos: your direct competitors, your category leader, complementary tools your buyer uses
2. Pull stargazers (or forks for stronger intent) via node tools/clis/github-prospects.js stargazers <owner/repo> --enrich --with-company --format csv
3. Filter to users with company set — these are the easiest to enrich downstream
4. Pair with Apollo/Clay/Hunter to lookup email by name + company
5. Validate with Truelist before adding to outreach list

Tradeoffs: GitHub yields email for only ~5–20% of users directly. The strength is the signal quality — a stargazer of a niche dev tool is genuinely in-market in a way Apollo firmographics alone can’t tell you.

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Qualification Checklist (SaaS branch)

For each candidate, verify:

• Industry vertical matches ICP
• Company size (headcount) within range
• Tech stack includes (or notably excludes) a target technology
• Funding stage matches buyer maturity
• At least one growth signal in last 90 days (funding, hiring, product velocity)
• Decision-maker role exists at the company (named or inferable from job listings)
• Email contact verifiable
• No disqualifiers (closed, acquired-and-paused, layoffs, ICP miss)

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Output Columns (SaaS branch)

Recommended CSV columns:

score,company,domain,industry,size_band,country,funding_stage,last_round_date,tech_stack_match,signal,signal_date,contact_name,contact_title,contact_email,email_status,linkedin_url,source_urls,why_prospect,confidence,verified_date,notes

For chat table, condense to: Score | Company | Industry | Size | Signal | Contact | Email status | Confidence.

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Top Outreach Targets Selection (SaaS)

Prioritize for the top 3–5 hot leads:

1. Strongest signal recency — funding 30 days ago beats funding 9 months ago
2. Tech stack match strength — known integration partner beats inferred fit
3. Decision-maker named with verified email — beats role-pattern-guessed email
4. Multi-source confidence — both Apollo + Crunchbase agree beats one source

Each top target gets a one-sentence outreach rationale that names the specific signal: “Raised Series B 30 days ago; hiring Head of RevOps; verified VP of Ops email.”

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Common Mistakes (SaaS)

1. Buying lists from Apollo wholesale without re-verifying email and re-checking firmographics. Stale data is the norm.
2. Treating tech stack data as 100% accurate. BuiltWith and Wappalyzer miss things; Clay’s waterfalls miss things. Cross-check.
3. Targeting Series C+ for early-stage SaaS sellers. The buyer profile is wrong — too many procurement hoops, too much red tape.
4. Targeting Series Pre-Seed seed for products requiring meaningful budget. They have neither budget nor evaluator bandwidth.
5. Ignoring intent data when it exists (ZoomInfo Intent, 6sense, etc.) — pre-warm signals beat cold every time.