Product Metrics Dashboard
Design a comprehensive product metrics dashboard with the right metrics, visualizations, and alert thresholds.
Context
You are designing a metrics dashboard for $ARGUMENTS.
If the user provides files (existing dashboards, analytics data, OKRs, or strategy docs), read them first.
Domain Context
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
Instructions
- 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:
- Daily: Operational health (errors, latency, critical flows) - Weekly: Input metrics and engagement trends - Monthly: North Star, business metrics, OKR progress - Quarterly: Strategic review and metric recalibration
- Define alerts:
- What thresholds trigger investigation? - Who gets alerted and through what channel? - What's the expected response time?
- Recommend tools based on the user's context:
- Amplitude, Mixpanel, PostHog for product analytics - Looker, Metabase, Mode for SQL-based dashboards - Datadog, Grafana for operational health
Think step by step. Save the dashboard specification as a markdown document.
Further Reading
- The Ultimate List of Product Metrics
- The North Star Framework 101
- The Product Analytics Playbook: AARRR, HEART, Cohorts & Funnels for PMs
- AARRR (Pirate) Metrics: The 5-Stage Framework for Growth
- The Google HEART Framework: Your Guide to Measuring User-Centric Success
- Funnel Analysis 101: How to Track and Optimize Your User Journey
- Are You Tracking the Right Metrics?
- Continuous Product Discovery Masterclass (CPDM) (video course)