product-analyst
Expert product analytics strategist for SaaS and digital products. Use when designing product metrics frameworks, funnel analysis, cohort retention, feature adoption tracking, A/B testing, experimentation design, data instrumentation, or product dashboards. Covers AARRR, HEART, behavioral analytics, and impact measurement.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/ncklrs/startup-os-skills --skill product-analyst- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads product-analyst automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Product Analyst
Strategic product analytics expertise for data-driven product decisions — from metrics framework selection to experimentation design and impact measurement.
Philosophy
Great product analytics isn't about tracking everything. It's about measuring what matters to drive better product decisions.
The best product analytics:
- Start with decisions, not data — What will you do differently based on this metric?
- Instrument once, measure forever — Invest in solid event tracking upfront
- Balance leading and lagging — Predict outcomes, don't just report them
- Make data accessible — Self-serve dashboards beat SQL queues
- Experiment before you ship — Validate hypotheses with real users
How This Skill Works
When invoked, apply the guidelines in rules/ organized by:
metrics-*— Frameworks (AARRR, HEART), KPI selection, metric hierarchiesfunnel-*— Conversion analysis, drop-off diagnosis, optimizationcohort-*— Retention analysis, segmentation, lifecycle trackingfeature-*— Adoption tracking, usage patterns, feature successexperiment-*— A/B testing, hypothesis design, statistical rigorinstrumentation-*— Event tracking, data modeling, collection best practicesdashboard-*— Visualization, stakeholder reporting, self-serve analytics
Core Frameworks
AARRR (Pirate Metrics)
| Stage | Question | Key Metrics |
|---|---|---|
| Acquisition | Where do users come from? | Traffic sources, CAC, signup rate |
| Activation | Do they have a great first experience? | Time-to-value, setup completion, aha moment |
| Retention | Do they come back? | DAU/MAU, D1/D7/D30 retention, churn |
| Revenue | Do they pay? | Conversion rate, ARPU, LTV |
| Referral | Do they tell others? | NPS, referral rate, viral coefficient |
HEART Framework (Google)
| Dimension | Definition | Signal Types |
|---|---|---|
| Happiness | User attitudes, satisfaction | NPS, CSAT, surveys |
| Engagement | Depth of involvement | Sessions, time-in-app, actions/session |
| Adoption | New users/features uptake | New users, feature adoption % |
| Retention | Continued usage over time | Retention curves, churn rate |
| Task Success | Efficiency and completion | Task completion, error rate, time-on-task |
The Metrics Hierarchy
┌─────────────────┐
│ North Star │ ← Single metric that matters most
│ Metric │
├─────────────────┤
│ Primary │ ← 3-5 key performance indicators
│ KPIs │
├─────────────────┤
│ Supporting │ ← Diagnostic and health metrics
│ Metrics │
├─────────────────┤
│ Operational │ ← Day-to-day tracking
│ Metrics │
└─────────────────┘
Retention Analysis Types
┌───────────────────────────────────────────────────────────┐
│ RETENTION VIEWS │
├───────────────────────────────────────────────────────────┤
│ N-Day Retention │ % who return on exactly day N │
│ Unbounded │ % who return on or after day N │
│ Bracket Retention │ % who return within a time window │
│ Rolling Retention │ % still active after N days │
└───────────────────────────────────────────────────────────┘
Experimentation Rigor Ladder
| Level | Approach | When to Use |
|---|---|---|
| 1. Gut | Ship and hope | Never for important features |
| 2. Qualitative | User research, feedback | Early exploration |
| 3. Observational | Pre/post analysis | Low-risk changes |
| 4. Quasi-experiment | Cohort comparison | When randomization hard |
| 5. A/B Test | Randomized control | Optimization, validation |
| 6. Multi-arm Bandit | Adaptive allocation | When speed > precision |
Metric Selection Criteria
| Criterion | Question | Good Sign |
|---|---|---|
| Actionable | Can we influence this? | Direct lever exists |
| Accessible | Can we measure it reliably? | <5% missing data |
| Auditable | Can we debug anomalies? | Clear calculation logic |
| Aligned | Does it tie to business value? | Executive cares |
| Attributable | Can we trace changes to causes? | A/B testable |
Anti-Patterns
- Vanity metrics — Tracking what looks good, not what drives decisions
- Metric overload — 50 dashboards, zero insights
- Lagging only — Measuring outcomes without predictive indicators
- Silent failures — No alerting on data quality issues
- HiPPO-driven — Highest-paid person's opinion beats data
- P-hacking — Running tests until you get significance
- Ship and forget — Launching features without success criteria
- Segment blindness — Looking only at averages, missing cohort differences
FAQ
What does the product-analyst skill do?
Expert product analytics strategist for SaaS and digital products. Use when designing product metrics frameworks, funnel analysis, cohort retention, feature adoption tracking, A/B testing, experimentation design, data instrumentation, or product dashboards. Covers AARRR, HEART, behavioral analytics, and impact measurement.
How do I install product-analyst?
Run npx skills add https://github.com/ncklrs/startup-os-skills --skill product-analyst in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/product-analyst/ (personal) or .claude/skills/product-analyst/ (project).
Which AI agents can use product-analyst?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is product-analyst safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains product-analyst?
It is published by ncklrs in ncklrs/startup-os-skills. It has 199 recorded installs.
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