Mmcp.market

metrics-dashboard skill

by phuryn·phuryn/pm-skills·27k stars·MIT

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.

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Install the metrics-dashboard skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/phuryn/pm-skills.git /tmp/pm-skills
mkdir -p ~/.claude/skills
cp -r /tmp/pm-skills/pm-product-discovery/skills/metrics-dashboard ~/.claude/skills/metrics-dashboard
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

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

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