Use-case selling

Contents

We sell products. Customers buy solutions.

When we pitch "add Surveys," it sounds like we're trying to increase their bill. When we pitch "here's how to close the loop on why users drop off," it sounds like we're solving their problem. Same product. Different framing. Very different conversion rate.

Use cases are how we sell. Products are how we bill. A use case is a discrete problem a team is trying to solve, supported by a combination of PostHog products. Billing, metering, and packaging don't change. What changes is how we talk about it, how we organize around it, and how we measure adoption.

Each use case has a full playbook with discovery questions, competitive positioning, expansion paths, objection handling, and onboarding checklists.

The seven use cases

Use caseJob to be doneCore buyer
Product Intelligence"Help me understand what users do, why they do it, and what to build next."PMs, designers, product engineers, founders
Release Engineering"Help me ship faster without breaking things."Engineering managers, platform teams, developers
Observability"Help me know when things break, understand why, and fix them fast."SREs, platform engineers, DevOps
Growth & Marketing"Help me understand what drives acquisition, conversion, and revenue."Growth engineers, marketing leads, CRO, GTM engineers
AI/LLM Observability"Help me understand how my AI features perform, what they cost, and how users interact with them."AI/ML engineers, AI PMs, AI founders
Data Infrastructure"Help me unify product data with business data and get it where it needs to go."Data engineers, analytics engineers, product ops
Customer Experience"Help me handle customer conversations in one place, understand what happened, and ship the fix."Support leaders, engineering leads, CS leaders

Product coverage matrix

ProductPrimary use caseSecondary use cases
SupportCustomer Experience
Product AnalyticsProduct IntelligenceGrowth & Marketing, AI/LLM Obs, Customer Experience
Session ReplayProduct IntelligenceRelease Engineering, Observability, AI/LLM Obs, Customer Experience
HeatmapsProduct IntelligenceGrowth & Marketing, Customer Experience
Feature FlagsRelease EngineeringGrowth & Marketing
ExperimentsRelease EngineeringProduct Intelligence, AI/LLM Obs, Growth & Marketing, Customer Experience
Error TrackingObservabilityAI/LLM Obs, Customer Experience
SurveysProduct IntelligenceGrowth & Marketing, Customer Experience
Web AnalyticsGrowth & Marketing
Marketing Analytics betaGrowth & Marketing
Customer Analytics beta (B2B mode requires Group Analytics add-on)Growth & MarketingProduct Intelligence
WorkflowsGrowth & MarketingProduct Intelligence, Customer Experience
AI ObservabilityAI/LLM ObsCustomer Experience
AI EvalsAI/LLM ObsProduct Intelligence, Release Engineering
Prompt management betaAI/LLM Obs
Data WarehouseData Infrastructure
Data Pipelines / Batch ExportsData InfrastructureGrowth & Marketing
Endpoints betaData Infrastructure
Semantic layer alphaData Infrastructure
LogsObservabilityCustomer Experience
Distributed tracing alphaObservabilityRelease Engineering
Metrics alphaObservability
Health checks betaObservabilityData Infrastructure
Replay VisionProduct IntelligenceCustomer Experience, Observability
PostHog AIHorizontal (all)
self-drivingHorizontal (all)Converts fastest in Observability, Release Engineering, and Customer Experience

Maturity matters when you're pitching. Anything marked alpha or beta above needs a caveat in the room, and each playbook carries the specific one. Two are worth knowing before any call:

  • Replay Vision is generally available — no waitlist, but usage is metered in credits against a monthly budget, so scope scanners narrowly. See quota and limits.
  • self-driving is a capability, not a SKU. Write it lowercase and hyphenated, and keep the customer's product as the subject: we make their product self-driving. Never "PostHog is a self-driving product." See brand foundations and how to pitch self-driving.

Products vs tools. In brand terms, most rows above are tools — the capabilities you access through the five products (PostHog Web, Slack, MCP, CLI, and Desktop). That distinction doesn't change how you sell a use case, but it does change the words: don't call PostHog Desktop a tool, and don't call product analytics a product.

Playbook structure

Every use case playbook follows the same sections, so TAMs know where to find what they need:

  1. Job to be done
  2. What PostHog products are relevant (with doc links)
  3. Adoption and expansion paths
  4. Business impact
  5. Personas to target
  6. Signals in Vitally & PostHog
  7. Command of the Message (discovery, negative consequences, desired state, outcomes, metrics)
  8. Competitive positioning
  9. Pain points & known limitations
  10. Getting a customer started (evaluation scope, onboarding checklist)
  11. Cross-sell pathways to other use cases
  12. Internal resources
  13. Company archetype considerations

Two pages add an Objection handling section between 10 and 11 (Growth & Marketing and Customer Experience), and Data Infrastructure adds a data-maturity appendix at the end. Everything else is consistent across all seven.

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