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Help existing PostHog customers improve their PostHog instance. Triggers on "help [customer] improve their PostHog setup", "audit [company]'s PostHog instance", "create tracking plan for [company]", "design data schema for [customer]", or requests to improve analytics coverage, fix instrumentation gaps, expand PostHog usage, or build better insights for customers already using PostHog. Use when working with a customer who already has PostHog installed. Help existing PostHog customers get more value from their instance. This skill is for Customer Success, not sales — the customer already has PostHog installed, something isn't working well, and your job is to diagnose the gaps and give them a clear path forward.
What it does
- Workflow
- Step 1: Research
- Step 2: Current State
- Step 3: Customer Profile
- Step 4: Ideal Schema
- Step 5: Insights Plan
When to use it
- Triggers on "help [customer] improve their PostHog setup", "audit [company]'s PostHog instance", "create tracking plan for [company]", "design data schema for [customer]", or requests to improve…
- Use when working with a customer who already has PostHog installed.
Advantages
The skill’s files do not state this.
Usage examples
The skill’s files do not state this.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/posthog/posthog-onboarding/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip posthog-onboarding.zip -d .agents/skills
Documentation by PostHog
PostHog CS Improvement Skill
Help existing PostHog customers get more value from their instance. This skill is for Customer Success, not sales — the customer already has PostHog installed, something isn't working well, and your job is to diagnose the gaps and give them a clear path forward.
Core assumption: Their current implementation is probably underinstrumented, inconsistently named, or not being used by the right people. Start from that baseline.
Workflow
Research – Understand what the company builds
Current State – Ask the customer to describe their setup and pain points
Customer Profile – Synthesize into a structured profile
Ideal Schema – Design best-in-class events and properties for their business type
Insights Plan – Prescribe insights by problem + maturity (see
references/insights-plan.md)Improvement Plan – Prioritized, actionable recommendations
Output – Customer-facing improvement plan
Writing Style: Follow references/writing-style.md for all outputs. Conversational and direct — not corporate, not salesy.
Step 1: Research
When triggered with a company name or domain, research:
What they build (product/service)
Their customers (B2B/B2C, market)
Business model (pricing, signup flow)
Tech signals (job postings, docs, stack)
Determine business type: B2B SaaS, B2C SaaS, E-commerce, Marketplace, Developer Tools, Fintech, Healthcare, Content/Media
See references/business-types.md for events and metrics by type.
Step 2: Current State
The goal here is to understand what's broken, missing, or ignored — not to validate what's working. Ask questions that surface problems.
Ask 2–3 questions max per message. Skip anything already known from research or context.
Must-Have
| Context | Why | Question |
|---|---|---|
| Primary pain point | Drives everything | "What's the #1 thing PostHog isn't giving you right now?" |
| Key user journeys | Core of any tracking plan | "What are the 2–3 most important flows in your product?" |
| Current events | Identifies gaps | "What events are you tracking today? What do you wish you were tracking?" |
| Who uses PostHog | Shapes recommendations | "Which teams actually open PostHog — and which ones should but don't?" |
| Products in use | Finds expansion areas | "Which PostHog products are you actively using vs. ignoring?" |
Should-Have
How long they've had PostHog
Whether engineers are engaged or if CS/PM are blocked waiting for instrumentation
Any previous attempts to fix the problem that didn't stick
Compliance constraints
Step 3: Customer Profile
## Customer Profile: [Company]
### Overview
- **Business Type:** [type]
- **What They Build:** [1–2 sentences]
- **Their Customers:** [B2B/B2C, who]
- **Revenue Model:** [subscription/usage/etc]
- **Stage:** [Seed/A/B, employee count]
### PostHog Setup
- **Time Using PostHog:** [months/years]
- **Products Active:** [Analytics, Replay, Flags, Experiments, Surveys, etc]
- **Analytics Maturity:** [Beginner/Intermediate/Advanced]
- **Who Uses PostHog:** [roles]
- **Who Doesn't (But Should):** [roles being left out]
### Current State
- **What They Think Is Working:** [their perception]
- **Primary Pain Point:** [the #1 problem, in their words]
- **Likely Gaps:** [based on what they told you — missing events, underused products, no dashboards, wrong people]
### Technical Context
- **Stack:** [web/mobile/backend, frameworks]
- **User Volume:** [DAU/MAU or events/month if known]
- **Compliance:** [requirements if any]
### Their Product
- **Key Journeys:** [1] [2] [3]
- **Activation Metric:** [what success looks like for their users]Step 4: Ideal Schema
Don't try to audit what they have — you don't have visibility into their data. Instead, design the best-in-class schema for their business type and key journeys, then use it as a benchmark. The customer can map their current tracking against it.
See references/data-schema.md for full property lists, group schemas, and AARRR event templates.
See references/business-types.md for events and metrics specific to their business type.
What to design
Person properties — what you'd want to know about every user (role, plan, signup source, activation status, etc.)
Group properties — for B2B: org name, plan, seat count, MRR, health score
Core events — cover the full AARRR journey for their product type:
Acquisition: how users arrive and sign up
Activation: the moment they first get value
Retention: the actions that predict they'll come back
Referral: sharing, inviting, expanding
Revenue: upgrade, purchase, renewal
Key properties on each event — include context that makes the event useful: source, method, plan, is_first_time, duration_seconds, etc.
Naming conventions
snake_casefor everythingis_prefix for booleans_countsuffix for numbers_atsuffix for timestampsBe specific:
subscription_upgradednotupgrade
Present this as: "Here's what great looks like for a company like yours — let's figure out how close you are."
Step 5: Insights Plan
Prescribe insights based on their pain point and maturity. See references/insights-plan.md for full detail.
Maturity Levels
Beginner: No analytics or just GA, no custom events, no dashboards Intermediate: Some events, knows funnels/cohorts, has used Mixpanel or Amplitude Advanced: Mature tracking, warehouse integration, running experiments
By Problem
| Problem | Beginner | Intermediate | Advanced |
|---|---|---|---|
| Churn | Retention chart, replays of churned users | Behavioral cohorts, correlation analysis | LTV analysis, churn prediction experiments |
| Trial conversion | Signup funnel, replays | Breakdown by source/plan | Exit surveys, A/B test CTAs |
| Onboarding | Step funnel, replays | Paths, device breakdown | A/B test flows, in-product surveys |
| Feature adoption | Usage trends, stickiness | Feature retention, power users | Correlation with retention |
| PMF | 12-week retention, WAU/MAU | Power user cohorts | Sean Ellis survey |
Always suggest 2–3 capabilities they're probably not using:
Session Replay with filters (most underused)
Correlation analysis
Feature flags for safe rollouts
In-product surveys
User paths
Group analytics for B2B accounts
Step 6: Improvement Plan
Prioritize by what unblocks the most value fastest. Frame as three phases:
Fix first (Days 1–7): Broken or missing events that are blocking any meaningful analysis. Naming fixes. Enabling products they already have access to.
Strengthen (Week 2–3): Add tracking for key journeys identified in Step 2. Build 2–3 core dashboards tied directly to their pain point. Get the right people in PostHog.
Expand (Week 3+): Add PostHog products they're not using (Flags, Experiments, Surveys). Deepen with group analytics or warehouse if relevant.
SDK reference (for instrumentation fixes)
| Stack | SDK | Notes |
|---|---|---|
| React/Next.js | posthog-js + Provider | Use PostHogProvider |
| Vue/Nuxt | posthog-js | Manual init |
| React Native | posthog-react-native | Handles persistence |
| Flutter | posthog-flutter | Dart |
| iOS | posthog-ios | Swift/ObjC |
| Android | posthog-android | Kotlin/Java |
| Node.js | posthog-node | Server-side |
| Python | posthog-python | Django/Flask/FastAPI |
Watch-outs
No engineering bandwidth to implement fixes — flag this early, don't build a plan that requires it
Pain point is vague — keep asking until it's specific and measurable
Tracking exists but no one looks at it — this is an insights gap, not a data gap; solve differently
The champion isn't actually using PostHog — whoever you're talking to needs to be a real user
Step 7: Output — Customer Improvement Plan
One document, shared with the customer. Conversational and direct — written like a PostHog doc, not a sales deck.
# PostHog improvement plan – [Company]
## What we're trying to fix
[One or two sentences. Name the problem specifically — not "improve analytics" but "understand why users churn in week 2" or "know which features drive retention."]
## Where you are now
[Honest, kind assessment. What's working, what isn't, and what's missing. Don't sugarcoat but don't be harsh. 3–5 sentences.]
## The ideal setup for a company like yours
[Brief description of what best-in-class looks like for their business type — reference the ideal schema from Step 4. Frame as "here's where you want to get to."]
## What we recommend
### Fix first
[2–3 specific, immediately actionable fixes. Name the event or property. Explain what it unlocks in one sentence.]
### Events to add
[Key missing events from the ideal schema. For each: event name, why it matters, one key property to include.]
### Insights to build
[3–5 specific insights tied to their pain point. Name the insight type, what question it answers.]
### Products to start using
[Any PostHog products they have access to but aren't using. One sentence on why each is relevant to their problem.]
## Your action plan
### Week 1
**Your team:**
- [ ] [Specific action + who owns it]
**We'll handle:**
- [ ] [What PostHog CS will do]
**End of week 1 goal:** [What "done" looks like]
### Week 2–3
[Next phase actions, same format]
## How we'll know it's working
| What | Target | How to check |
|------|--------|--------------|
| [Metric] | [Specific number or outcome] | [Where to look in PostHog] |Reference Files
references/data-schema.md– Person/group/event properties with stakeholder valuereferences/insights-plan.md– Insights by problem and maturityreferences/business-types.md– Events and metrics by business typereferences/writing-style.md– PostHog writing guidelines
Files
- ATTRIBUTION.mdAdded by AutoGineer869 B
- LICENSELicence file added by AutoGineer1.0 KiB
- README.md2.6 KiB
- SKILL.md10.3 KiB
- references/business-types.md7.2 KiB
- references/data-schema.md9.3 KiB
- references/insights-plan.md9.0 KiB
- references/sales-context.md2.1 KiB
- references/writing-style.md2.9 KiB
references/insights-plan.md
Insights Plan Reference
Prescribe specific insights based on customer's stated problem and analytics maturity.
Analytics Maturity Levels
Beginner
No analytics or just Google Analytics
No custom event tracking beyond pageviews
No dashboards or regular reporting
Team unfamiliar with product analytics concepts
Intermediate
Has used Mixpanel, Amplitude, or similar
Some custom event tracking in place
Basic dashboards exist
Knows what funnels/cohorts are
Advanced
Mature tracking plan with consistent naming
Data warehouse integration
Uses cohorts, experiments, feature flags
Has dedicated analytics/data person
Problem: "Understand why users churn"
| Maturity | Insight Type | Specific Insight | What It Shows | PostHog Feature |
|---|---|---|---|---|
| Beginner | Retention | Week-over-week retention by signup cohort | Basic retention patterns | Retention insight |
| Beginner | Replay | Recordings filtered to churned users | What they did before leaving | Session Replay |
| Beginner | Trend | Active users over time (7d, 30d) | Is retention improving? | Trends |
| Intermediate | Funnel | Activation funnel with conversion time | Where users drop off | Funnels |
| Intermediate | Cohort | "Did X" vs "Didn't do X" cohorts | Features correlated with retention | Cohorts |
| Intermediate | Retention | Retention by initial referrer/campaign | Which channels bring retained users | Retention |
| Advanced | Correlation | Funnel correlation analysis | Statistical churn predictors | Funnel correlation |
| Advanced | SQL | LTV by signup source | Which sources most valuable | SQL insights |
| Advanced | Experiment | Test onboarding variants | Prove changes improve retention | Experiments |
Quick Wins (< 30 min total)
Build retention chart (5 min)
Watch 10 replays of churned users (20 min)
Create "Active" vs "Churned" cohorts (5 min)
Problem: "Improve trial-to-paid conversion"
| Maturity | Insight Type | Specific Insight | What It Shows | PostHog Feature |
|---|---|---|---|---|
| Beginner | Funnel | Signup → Activation → Conversion | Where trials fail | Funnels |
| Beginner | Trend | Daily trial starts vs conversions | Conversion rate over time | Trends |
| Beginner | Replay | Trial users who didn't convert | What blocked them | Session Replay |
| Intermediate | Funnel | Onboarding steps funnel | Which steps cause drop-off | Funnels |
| Intermediate | Breakdown | Conversion by signup source | Which channels convert best | Trends + Breakdown |
| Intermediate | Retention | Trial engagement by day | When engagement drops | Retention |
| Advanced | Correlation | Trial behaviors → conversion | What predicts conversion | Correlation |
| Advanced | Experiment | Test pricing page variants | Optimize conversion | Experiments |
| Advanced | Survey | Exit survey for non-converters | Why they didn't convert | Surveys |
Quick Wins
Build trial funnel: Signup → [Activation] → Payment (10 min)
Add breakdown by signup_source (5 min)
Watch 5 replays of trials that dropped at activation (15 min)
Problem: "Improve onboarding completion"
| Maturity | Insight Type | Specific Insight | What It Shows | PostHog Feature |
|---|---|---|---|---|
| Beginner | Funnel | Onboarding steps (Step 1 → 2 → 3 → Done) | Where users drop off | Funnels |
| Beginner | Replay | Users who didn't complete onboarding | UX friction points | Session Replay |
| Beginner | Trend | Onboarding completion rate over time | Is it improving? | Trends |
| Intermediate | Breakdown | Completion by device type | Mobile vs desktop differences | Funnels + Breakdown |
| Intermediate | Path | Paths from signup to first feature | Actual vs designed flow | User Paths |
| Intermediate | Cohort | "Completed onboarding" vs "Skipped" | Behavioral differences | Cohorts |
| Advanced | Experiment | Test onboarding flow variants | A/B test improvements | Experiments |
| Advanced | Flag | Progressive onboarding rollout | Gradual improvement | Feature Flags |
| Advanced | SQL | Time-to-complete by cohort | Trend over time | SQL |
Quick Wins
Build step-by-step onboarding funnel (15 min)
Add breakdown by device_type (5 min)
Watch 5 replays of drop-offs at biggest friction point (10 min)
Problem: "Understand feature adoption"
| Maturity | Insight Type | Specific Insight | What It Shows | PostHog Feature |
|---|---|---|---|---|
| Beginner | Trend | Feature usage over time (each feature) | What's used most | Trends |
| Beginner | Stickiness | Days/week users use each feature | Feature engagement depth | Stickiness |
| Beginner | Replay | Users discovering features | How they find and use features | Session Replay |
| Intermediate | Retention | Feature-specific retention | Which features drive retention | Retention |
| Intermediate | Path | Paths to feature discovery | How users find features | User Paths |
| Intermediate | Breakdown | Usage by plan tier | Premium vs free behavior | Trends + Breakdown |
| Advanced | Correlation | Feature usage → retention | Which features matter most | Correlation |
| Advanced | Experiment | Test feature discovery flows | Improve adoption | Experiments |
| Advanced | Survey | Feature satisfaction surveys | Qualitative feedback | Surveys |
Quick Wins
Create feature usage dashboard with all major features (20 min)
Build stickiness chart for top 3 features (10 min)
Compare retention: users who used Feature X vs didn't (10 min)
Problem: "Measure product-market fit"
| Maturity | Insight Type | Specific Insight | What It Shows | PostHog Feature |
|---|---|---|---|---|
| Beginner | Retention | 12-week unbounded retention | Classic PMF metric | Retention |
| Beginner | Trend | WAU/MAU ratio | Engagement intensity | Trends (formula) |
| Beginner | Survey | NPS survey | Customer satisfaction | Surveys |
| Intermediate | Cohort | Power users (top 10% by usage) | Who loves the product | Cohorts |
| Intermediate | Stickiness | Days active per week distribution | Usage patterns | Stickiness |
| Intermediate | Retention | Retention by referral source | Organic vs paid quality | Retention |
| Advanced | Survey | "Very disappointed" % (Sean Ellis) | PMF survey metric | Surveys + SQL |
| Advanced | Correlation | Power user behaviors vs churned | What differentiates success | Correlation |
| Advanced | Lifecycle | New/Returning/Resurrecting/Dormant | User health distribution | Lifecycle |
Quick Wins
Build 12-week retention chart (10 min)
Calculate WAU/MAU ratio in trends (10 min)
Create "Power User" cohort (top 10% by events) (10 min)
Problem: "Replace [competitor tool]"
| Maturity | Insight Type | Specific Insight | What It Shows | PostHog Feature |
|---|---|---|---|---|
| All | Dashboard | Replicate their top 3 dashboards | Parity demonstration | Dashboards |
| All | Trend | Compare event counts to old tool | Data accuracy | Trends |
| All | Replay | Watch recordings (new capability) | Added value | Session Replay |
| All | Funnel | Recreate their key funnel | Workflow parity | Funnels |
| Intermediate | Cohort | Recreate their key segments | Cohort parity | Cohorts |
| Advanced | SQL | Complex queries from old tool | Query capability | SQL |
Quick Wins
List their top 3 dashboards, recreate first one (30 min)
Compare one key metric between tools (15 min)
Show session replay as net-new capability (10 min)
Bonus Capabilities
Always recommend 2-3 based on use case:
| Capability | When to Recommend | What It Unlocks | Pitch |
|---|---|---|---|
| Session Replay + Filters | Any UX problem | Watch exactly the sessions where something went wrong | "Filter replays to churned users and see what happened" |
| Correlation Analysis | Churn/conversion | Statistically identify success predictors | "Find behaviors that predict conversion without guessing" |
| Feature Flags | Deployment risk | Safe rollouts, instant rollback | "Ship to 10% of users, measure, then expand" |
| Experiments | A/B testing needs | Statistical significance, auto analysis | "Run real experiments with automatic winner detection" |
| Surveys | Qualitative gaps | In-product surveys triggered by events | "Ask users why right after they do something" |
| User Paths | Navigation confusion | Visualize actual user flows | "See real paths users take vs designed ones" |
| Lifecycle Analysis | Retention concerns | New/Returning/Dormant breakdown | "See if acquiring faster than churning" |
| Group Analytics | B2B multi-user | Account-level metrics | "Track companies, not just users" |
| Data Warehouse | External data | Combine PostHog with revenue/CRM | "Join Stripe data with product behavior" |
| HogQL (SQL) | Power users | Arbitrary event queries | "Query your data however you want" |
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Python, Needs Node.js
Security
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Attribution and licence
- Published by
- PostHog
- Publisher
- PostHog (Official)
- Source
- PostHog/skills · skills/team/customer-success/posthog-onboarding · commit a5d30e7
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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