# SaaS Prospecting Reference For when the user sells SaaS or digital services to other SaaS companies / digital businesses. --- ## 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) --- ## 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 --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. --- ## 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) --- ## Output Columns (SaaS branch) Recommended CSV columns: ```csv 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. --- ## 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." --- ## 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.