metrics-dashboard

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

1. 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

1. 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] |

1. 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] │ └─────────────────────────────────────────────┘ ``

1. Set review cadence:
2. Daily: Operational health (errors, latency, critical flows)
3. Weekly: Input metrics and engagement trends
4. Monthly: North Star, business metrics, OKR progress
5. Quarterly: Strategic review and metric recalibration

1. Define alerts:
2. What thresholds trigger investigation?
3. Who gets alerted and through what channel?
4. What's the expected response time?

1. Recommend tools based on the user's context:
2. Amplitude, Mixpanel, PostHog for product analytics
3. Looker, Metabase, Mode for SQL-based dashboards
4. 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)