Product Health Dashboard Designer

Overview

Design dashboards and metrics that tell the story of product health. Define KPIs, specify visualizations, and establish alerting that enables proactive product management.

Core principle: Measure what matters, not what's easy. A good dashboard enables decision-making, not just data display.

When to Use

• Product launching to production
• Redesigning existing analytics
• Onboarding new team to product metrics
• Quarterly health check methodology

Output Format

product_health_dashboard:
  product: "[Product name]"
  version: "[YYYY-MM-DD]"
  audience: "[Who uses this dashboard]"
  
  north_star:
    metric: "[Primary success metric]"
    definition: "[Exactly how it's calculated]"
    data_source: "[Where data comes from]"
    current: "[Current value]"
    target: "[Goal value]"
    refresh_rate: "[Real-time | Hourly | Daily]"
  
  kpis:
    - category: "[Acquisition | Activation | Engagement | Retention | Revenue]"
      metrics:
        - name: "[Metric name]"
          definition: "[Calculation formula]"
          data_source: "[Where from]"
          visualization: "[Number | Chart type]"
          healthy_range: "[X to Y]"
          warning_threshold: "[Trigger for concern]"
          critical_threshold: "[Trigger for action]"
          trend_period: "[Days/weeks to show]"
  
  dashboard_layout:
    sections:
      - section: "[Section name]"
        purpose: "[What decisions this enables]"
        components:
          - type: "[Big number | Line chart | Bar chart | Table]"
            metric: "[Metric name]"
            size: "[Full | Half | Quarter]"
            comparisons: ["[vs last period | vs target]"]
  
  alerts:
    - metric: "[Metric name]"
      condition: "[When to alert]"
      severity: "[Critical | Warning | Info]"
      channel: "[Slack | Email | PagerDuty]"
      recipients: ["[Team/person]"]
      runbook: "[Link to response procedure]"
  
  segments:
    - segment: "[User segment]"
      filter: "[How to identify]"
      rationale: "[Why this matters separately]"
  
  data_requirements:
    events: ["[Event name: description]"]
    properties: ["[Property: what it captures]"]
    implementation_notes: "[Technical requirements]"
  
  review_cadence:
    daily: "[What to check daily]"
    weekly: "[Weekly review focus]"
    monthly: "[Monthly deep dive]"

KPI Framework: AARRR

Acquisition

Activation

Engagement

Retention

Revenue

Dashboard Design Principles

Layout Hierarchy

┌────────────────────────────────────────────────────────────┐
│ NORTH STAR METRIC                                    BIG   │
│ [Primary success metric with trend]                        │
├────────────────────────────────────────────────────────────┤
│ KEY HEALTH INDICATORS                                      │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐        │
│ │ Metric 1     │ │ Metric 2     │ │ Metric 3     │        │
│ │ [Trend chart]│ │ [Trend chart]│ │ [Trend chart]│        │
│ └──────────────┘ └──────────────┘ └──────────────┘        │
├────────────────────────────────────────────────────────────┤
│ DETAILED VIEWS                                             │
│ [Segment breakdowns, cohort analysis, feature metrics]     │
└────────────────────────────────────────────────────────────┘

Visualization Selection

Alert Design

Threshold Setting

alert_thresholds:
  approach: "Statistical"
  method: "Mean ± 2 standard deviations over 30 days"
  
  example:
    metric: "Daily signups"
    mean: 100
    std_dev: 15
    warning_low: 70   # Mean - 2σ
    warning_high: 130 # Mean + 2σ
    critical_low: 55  # Mean - 3σ

Severity Levels

Alert Hygiene

alert_principles:
  - "Every alert should be actionable"
  - "If nobody acts, remove the alert"
  - "Review alert fatigue monthly"
  - "Each critical alert needs a runbook"

Segmentation Strategy

Common Segments

Segment Dashboard

segment_view:
  primary_segment: "User lifecycle"
  default_view: "Active users"
  comparison: "Side-by-side segment comparison"
  
  metrics_per_segment:
    - "Segment size"
    - "Key action rate"
    - "Revenue contribution"
    - "Trend vs previous period"

Implementation Checklist

Before Launch

• North star metric defined
• AARRR metrics specified
• Dashboard layout designed
• Alert thresholds set
• Data events specified
• Tracking implemented

After Launch

• Dashboard built and tested
• Alerts delivering correctly
• Team trained on interpretation
• Review cadence established
• Runbooks created for critical alerts

Common Mistakes