124 lines
5.9 KiB
Markdown
124 lines
5.9 KiB
Markdown
# SaaS Prospecting Reference
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For when the user sells SaaS or digital services to other SaaS companies / digital businesses.
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---
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## ICP Signals That Matter (SaaS branch)
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Beyond standard firmographics (industry, size, geography), SaaS prospects are qualified by:
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### Technographic signals
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- **Tech stack** — do they use complementary tools (your integration target) or competing tools (a switch opportunity)?
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- **Recent stack changes** — adding/removing tools signals active vendor evaluation
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- **Custom-built vs off-the-shelf** — DIY tooling often means a buyer who'd benefit from your product
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- **Free/freemium plan signals** — using a free competitor means they may be ready to upgrade
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### Growth signals
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- **Funding round** — Series A / B / C in last 6 months = budget + new hires + tool needs
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- **Headcount growth** — 10%+ growth in last quarter signals scaling pressure
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- **Hiring signals** — specific role openings (e.g., "Head of RevOps" → ICP for revops tooling)
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- **Product velocity** — frequent shipping, new features, blog posts = healthy growth motion
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- **Open positions for your buyer's role** — if you sell to Marketing Ops and they're hiring one, that's a signal
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### Decay signals (downgrade scoring)
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- Layoffs in target department
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- Funding round >2 years ago with no follow-up
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- Product hasn't shipped in 6+ months
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- Team page shows founders only (very early — may not have budget)
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---
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## Discovery Sources (SaaS branch)
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Combine 2+ sources for cross-verification.
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### Tier 1 — primary discovery
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- **Apollo**: firmographic + technographic + contact data. Good for building large initial lists.
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- **Clay**: waterfall enrichment, custom scoring, multi-source merges. Best for high-quality smaller lists.
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- **ZoomInfo**: enterprise-grade firmographic + intent signals. Expensive; mid-market+.
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- **LinkedIn Sales Navigator**: decision-maker mapping. Use manually, never bulk scrape.
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### Tier 2 — technographic / growth signals
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- **BuiltWith**: tech stack lookups, find sites using specific tools
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- **Wappalyzer**: free browser extension + API; lighter tech stack signal
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- **Crunchbase**: funding rounds, headcount, founders
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- **Pitchbook**: deeper investor data (enterprise/paid)
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- **ProductHunt**: recent launches, builder audience
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- **Hacker News / Show HN**: technical builders launching products
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### Tier 3 — buying signals
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- **Job boards** (LinkedIn Jobs, Indeed, AngelList): role openings as signals
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- **RB2B / Clearbit Reveal**: visitor identification (warm anonymous traffic)
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- **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.
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- **Recent blog posts / changelog**: product direction signals
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- **G2 reviews mentioning competitor switches**: explicit dissatisfaction signal
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#### GitHub prospecting pattern (when audience is developers)
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For dev-tool SaaS, GitHub is one of the highest-quality discovery channels:
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1. Identify 3–5 "anchor" repos: your direct competitors, your category leader, complementary tools your buyer uses
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2. Pull stargazers (or forks for stronger intent) via `node tools/clis/github-prospects.js stargazers <owner/repo> --enrich --with-company --format csv`
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3. Filter to users with `company` set — these are the easiest to enrich downstream
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4. Pair with Apollo/Clay/Hunter to lookup email by name + company
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5. Validate with Truelist before adding to outreach list
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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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---
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## Qualification Checklist (SaaS branch)
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For each candidate, verify:
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- [ ] Industry vertical matches ICP
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- [ ] Company size (headcount) within range
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- [ ] Tech stack includes (or notably excludes) a target technology
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- [ ] Funding stage matches buyer maturity
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- [ ] At least one growth signal in last 90 days (funding, hiring, product velocity)
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- [ ] Decision-maker role exists at the company (named or inferable from job listings)
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- [ ] Email contact verifiable
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- [ ] No disqualifiers (closed, acquired-and-paused, layoffs, ICP miss)
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---
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## Output Columns (SaaS branch)
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Recommended CSV columns:
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```csv
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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
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```
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For chat table, condense to: Score | Company | Industry | Size | Signal | Contact | Email status | Confidence.
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---
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## Top Outreach Targets Selection (SaaS)
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Prioritize for the top 3–5 hot leads:
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1. **Strongest signal recency** — funding 30 days ago beats funding 9 months ago
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2. **Tech stack match strength** — known integration partner beats inferred fit
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3. **Decision-maker named with verified email** — beats role-pattern-guessed email
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4. **Multi-source confidence** — both Apollo + Crunchbase agree beats one source
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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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---
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## Common Mistakes (SaaS)
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1. **Buying lists from Apollo wholesale** without re-verifying email and re-checking firmographics. Stale data is the norm.
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2. **Treating tech stack data as 100% accurate**. BuiltWith and Wappalyzer miss things; Clay's waterfalls miss things. Cross-check.
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3. **Targeting Series C+ for early-stage SaaS sellers**. The buyer profile is wrong — too many procurement hoops, too much red tape.
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4. **Targeting Series Pre-Seed seed** for products requiring meaningful budget. They have neither budget nor evaluator bandwidth.
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5. **Ignoring intent data when it exists** (ZoomInfo Intent, 6sense, etc.) — pre-warm signals beat cold every time.
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