01 · Land & expand (Free / Indie)
Land on Free or Indie — graduate to Pro on the same Agentic Revenue OS.
Who: Solo or two-person teams who need Pipeline proof without a GTM stack, contact database, or ad budget — Scout → Closer on the same runtime RevOps teams run at scale.
Graph surfaces:
- Evaluation threads in your category
- Community and forum posts asking for tool recommendations
- Public switching and pricing-pain conversations
Typical Graph → play: "Is there a tool for X that doesn't require a full outbound stack?" → Scout elevate + Closer motion that mirrors the asker's language.
Outcome: Pipeline attribution within 72 hours — Graph → Scout → Closer, no list purchase or separate toy product.
02 · Product Behavior Intelligence
Revenue Protected and Expansion from product behavior — not another dashboard.
Who: Product-led SaaS, sales-assisted PLG, and CS teams who need per-company usage truth — Keeper and Grower on the same Revenue Graph.
Graph surfaces:
- First-party product events (SDK, Segment, PostHog)
- Workspace and team adoption inside the product
- Revenue and expansion signals tied to usage thresholds
Typical Graph → play: Usage drops 40% at Acme → churn-risk play queued · Fortis adds two teams on a sticky feature → expansion play recommended.
Outcome: At Risk and Expansion missions queue with approval and audit — Protected and Expansion $ before renewal surprises.
03 · B2B SaaS founders
Pipeline from in-market Graph signals — not Apollo seat tax for sub-1% conversion.
Who: Founder-led B2B SaaS teams (5–25) replacing outbound lists with Revenue Graph qualification and Scout → Closer handoffs.
Graph surfaces:
- Category evaluation communities
- “Alternatives to X” threads
- Product-comparison Q&A
Typical Graph → play: "Any alternative to [incumbent]?" → contextual Closer reply + attributed landing against the named incumbent.
Outcome: Pipeline $ from accounts that raised their hand — CAC drops because Scout elevates DNA matches.
04 · Dev-tool & API companies
Your buyers live in technical threads, not inboxes.
Who: Dev-tool, API, and infra companies whose ICP is engineers.
Graph surfaces:
- Technical forums and Q&A
- GitHub issues asking for libraries in your category
- Stack-specific communities
Typical Graph → play: "What's the best [thing] for [their stack]?" → technical Scout draft + Closer page tuned to stack.
Outcome: Pipeline signups arrive with Graph context and DNA match — trust earned where engineers evaluate.
05 · AI-app builders
Win “which AI for X?” at the moment of intent.
Who: AI-app teams who need comparison signals as the category moves weekly.
Graph surfaces:
- AI comparison communities
- Launch comments comparing apps
- “Any AI for [task]?” threads
Typical Graph → play: "Is there an AI app that does [task]?" → real answer + attributed page mirroring their use case.
Outcome: Scout routes fast-moving category asks — Pipeline from DNA match, not competitor tag wars.
06 · OSS maintainers monetizing
Free users everywhere. Paying users have a deadline. Find them.
Who: OSS maintainers turning a popular library into a hosted/paid product.
Graph surfaces:
- GitHub issues with production / budget language
- Self-host and ops communities
- “How do you handle X at scale” threads
Typical Graph → play: Thread mentions production scale or commercial use → clear OSS → hosted path + stack-tuned page.
Outcome: OSS stays free; paid conversions come from intent-qualified Graph signals.
07 · Agencies & freelancers
Show up in context before the shortlist.
Who: Boutique agencies and senior freelancers winning work where prospects ask publicly.
Graph surfaces:
- Hiring and founder recommendation threads
- Indie maker communities
- Vendor-ask conversations
Typical Graph → play: "Looking for a [craft] studio for [project]" → expert reply + page for that project shape.
Outcome: Shorter cycle: you arrive when they're shopping, not three weeks later in a cold inbox.
Product Behavior Intelligence deep dive: Open playbook →