Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan.
Instructions your experts follow when using this skill.
Packaging adaptation by AutoGPT, 2026-09-25. Original authorship and licence are retained. Changes are limited to the recorded name, metadata and local references; see ATTRIBUTION.md in this package.
Design a comprehensive product metrics dashboard with the right metrics, visualizations, and alert thresholds.
You are designing a metrics dashboard for $ARGUMENTS.
If the user provides files (existing dashboards, analytics data, OKRs, or strategy docs), read them first.
Metrics vs KPIs vs NSM: Metrics = all measurable things. KPIs = a few key quantitative metrics tracked over a longer period. North Star Metric = a single customer-centric KPI that is a leading indicator of business success.
4 criteria for a good metric (Ben Yoskovitz, Lean Analytics): (1) Understandable — creates a common language. (2) Comparative — over time, not a snapshot. (3) Ratio or Rate — more revealing than whole numbers. (4) Behavior-changing — the Golden Rule: "If a metric won't change how you behave, it's a bad metric."
8 metric types: Vanity vs Actionable (only actionable metrics change behavior), Qualitative vs Quantitative (WHAT vs WHY — you need both; never stop talking to customers), Exploratory vs Reporting (explore data to uncover unexpected insights), Lagging vs Leading (leading indicators enable faster learning cycles, e.g. customer complaints predict churn).
5 action steps: (1) Audit metrics against the 4 good-metric criteria. (2) Update dashboards — ensure all key metrics are good ones. (3) Identify vanity metrics — be careful how you use them. (4) Classify leading vs lagging indicators. (5) Pick one problem and dig deep into the data.
For case studies and more detail: Are You Tracking the Right Metrics? by Ben Yoskovitz
Identify the metrics framework — organize metrics into layers:
North Star Metric: The single metric that best captures core value delivery
Input Metrics (3-5): The levers that drive the North Star
Health Metrics: Guardrails that ensure overall product health
Business Metrics: Revenue, cost, and unit economics
For each metric, define:
| Metric | Definition | Data Source | Visualization | Target | Alert Threshold |
|---|---|---|---|---|---|
| [Name] | [Exact calculation: numerator/denominator, time window] | [Where the data comes from] | [Line chart / Bar / Number / Funnel] | [Goal value] | [When to trigger an alert] |
Design the dashboard layout:
┌─────────────────────────────────────────────┐
│ NORTH STAR: [Metric] — [Current Value] │
│ Trend: [↑/↓ X% vs last period] │
├──────────────────┬──────────────────────────┤
│ Input Metric 1 │ Input Metric 2 │
│ [Sparkline] │ [Sparkline] │
├──────────────────┼──────────────────────────┤
│ Input Metric 3 │ Input Metric 4 │
│ [Sparkline] │ [Sparkline] │
├──────────────────┴──────────────────────────┤
│ HEALTH: [Latency] [Error Rate] [NPS] │
├─────────────────────────────────────────────┤
│ BUSINESS: [MRR] [CAC] [LTV] [Churn] │
└─────────────────────────────────────────────┘
Set review cadence:
Define alerts:
Recommend tools based on the user's context:
Think step by step. Save the dashboard specification as a markdown document.
Files installed alongside these instructions.
When the user wants to create or update their product marketing context document. Also use when the user mentions 'product context,' 'marketing context,' 'set up context,' 'positioning,' 'who is my target audience,' 'describe my product,' 'ICP,' 'ideal customer profile,' or wants to avoid repeating foundational information across marketing tasks. Use this at the start of any new project before using other marketing skills — it creates `.agents/product-marketing.md` that all other skills reference for product, audience, and positioning context.
When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files. For creating comparison/alternative pages from profiles, see competitors. For sales-specific battle cards, see sales-enablement.
When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," "PMF survey," "product/market fit survey," "customer interview questions," "interview outreach," "Sales Safari," or "find out why customers churn/convert/buy." Use for analyzing existing research assets, mining online sources, AND running primary research (interviews and surveys). For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.