Dashboard Design Workflow

Purpose

Design a structured set of metrics across the user lifecycle that gives a complete picture of product health, not just a single North Star. Creates recurring dashboards for team reviews, early problem detection, and strategic decision-making.

When to Use This Workflow

Use this workflow when:

•Standing up a new product team and need recurring dashboard
•Existing dashboard feels incomplete or unfocused
•Preparing for quarterly business reviews
•Onboarding to a product and want to understand what "healthy" looks like
•Establishing metrics for ongoing product monitoring
•Need to rally team around clear success indicators

Skills Sequence

This workflow orchestrates 4 core skills:

code

1. North Star Alignment
   ↓ (Anchor dashboard to company mission and business model)
2. Funnel-Based Metric Mapping
   ↓ (Ensure coverage across all lifecycle stages)
3. Proxy Metric Selection
   ↓ (Pick measurable indicators for each stage)
4. Trade-off Evaluation
   ↓ (Include counter-metrics to catch unintended effects)
   
OUTPUT: Dashboard structure by funnel, 5-10 metrics with definitions,
        counter-metrics, review cadence, alert thresholds

Required Inputs

Gather this information before starting:

Product Context

•
Company/product mission statement
- •What's the overarching goal?
•
Business model type
- •One of 5 categories (ads, freemium, SaaS, marketplace, e-commerce)
•
Strategic priorities
- •Growth, retention, monetization, quality?

Product Lifecycle

•
User lifecycle stages for this product
- •How do users progress through your product?
- •What's the journey from awareness to retained power user?

Current State

•
Existing metrics (if any)
- •What are you currently tracking?
- •What gaps exist?
•
Key stakeholder questions
- •What questions should dashboard answer?
- •What decisions does it inform?

Operational Constraints

•
Review cadence desired
- •Daily, weekly, monthly?
- •Different cadences for different audiences?
•
Alert capability
- •Can you set automated alerts?
- •What thresholds trigger escalation?

Workflow Steps

Step 1: North Star Anchoring (15 minutes)

Use the north-star-alignment skill

Ground the dashboard in company-level goals:

Activities:

•Identify business model and corresponding North Star metrics
•Articulate how this product serves company mission
•Define "healthy" for this product relative to North Star

Questions to answer:

•What company-level metrics does this product impact?
•How does product health translate to company health?
•What would "great" look like for this product?
•What's the connection between product and company success?

Output:

markdown

## North Star Anchoring

**Business Model:** [Type]

**Company North Star Metrics:**
- [Metric 1]: [Definition]
- [Metric 2]: [Definition]

**Product's North Star Connection:**
- This product contributes to [Company North Star] by [mechanism]
- "Healthy" product = [Description tied to North Star]

**Mission Alignment:**
- Product serves mission: [How]
- Strategic priority: [Growth/Retention/Monetization/Quality]

Step 2: Funnel Structure Mapping (20 minutes)

Use the funnel-metric-mapping skill

Decompose user journey into stages and identify metrics per stage:

Activities:

•Define lifecycle stages (typically 4-5 stages)
•List 1-3 key metrics per stage
•Identify transition conversion rates
•Map any flywheel dynamics

Funnel template:

code

Reach → Activation → Engagement (Breadth) → Engagement (Depth) → Retention

For each stage, ask:

•What defines success at this stage?
•What volume metric matters?
•What quality metric matters?
•What's the conversion rate to next stage?

Output:

markdown

## Funnel Structure

**Stage 1: Reach**
- Definition: [When users become aware/access product]
- Key Metrics:
  1. [Metric]: [Definition + why it matters]
  2. [Metric]: [Definition + why it matters]
- Conversion to Activation: [%]

**Stage 2: Activation**
- Definition: [When users complete setup and reach first value]
- Key Metrics:
  1. [Metric]: [Definition + why it matters]
  2. [Metric]: [Definition + why it matters]
- Conversion to Engagement: [%]

**Stage 3: Engagement (Breadth)**
- Definition: [Regular product usage]
- Key Metrics:
  1. [Metric]: [Definition + why it matters]
  2. [Metric]: [Definition + why it matters]

**Stage 4: Engagement (Depth)**
- Definition: [Value-creating actions]
- Key Metrics:
  1. [Metric]: [Definition + why it matters]
  2. [Metric]: [Definition + why it matters]

**Stage 5: Retention**
- Definition: [Long-term repeat usage]
- Key Metrics:
  1. [Metric]: [Definition + why it matters]
  2. [Metric]: [Definition + why it matters]

**Flywheel Dynamics:**
- [If applicable, describe virtuous cycles]

Step 3: Proxy Metric Selection (20 minutes)

Use the proxy-metric-selection skill

For each funnel stage, define precise measurable indicators:

Activities:

•For each metric, define mathematical formula (numerator/denominator)
•Create simplified alternatives where needed
•Validate each metric is actionable by the team
•Ensure leading indicators (not just lagging)

Criteria for dashboard metrics:

•Actionable: Team can directly influence
•Understandable: Explainable in one sentence
•Measurable: Clear data source
•Leading: Provides early signal, not just hindsight

Output:

markdown

## Metric Definitions

**Reach Metrics:**

**1. [Metric Name]**
- Formula: [Numerator] / [Denominator]
- Data Source: [Where to measure]
- Actionability: [How team influences]
- Why it matters: [Connection to funnel stage goal]

**2. [Metric Name]**
[Same structure]

**Activation Metrics:**
[1-2 metrics with same detail]

**Engagement (Breadth) Metrics:**
[1-2 metrics with same detail]

**Engagement (Depth) Metrics:**
[1-2 metrics with same detail]

**Retention Metrics:**
[1-2 metrics with same detail]

Step 4: Counter-Metric Identification (15 minutes)

Use the tradeoff-evaluation skill

Identify metrics that could indicate unintended consequences:

Activities:

•For each primary metric, ask "what could go wrong?"
•Identify cannibalization risks
•Define acceptable ranges
•Plan monitoring approach

Counter-metric categories:

•
Cannibalization Metrics
- •What other products/features might suffer?
- •Example: New feature adoption hurting core feature usage
•
Quality Degradation Metrics
- •What quality indicators could decline?
- •Example: Growth at expense of user satisfaction
•
Sustainability Metrics
- •What could indicate unsustainable growth?
- •Example: High churn masked by high acquisition
•
Balance Metrics (for marketplaces)
- •Supply vs. demand balance
- •Example: Too many drivers, not enough riders

Output:

markdown

## Counter-Metrics

**For Primary Metric: [Name]**
- Counter-metric 1: [Name]
  - What it catches: [Unintended effect]
  - Acceptable range: [Threshold]
  - Alert if: [Condition]

**For Primary Metric: [Name]**
- Counter-metric 2: [Name]
  - What it catches: [Unintended effect]
  - Acceptable range: [Threshold]
  - Alert if: [Condition]

[2-3 counter-metrics total]

**Cannibalization Watch:**
- [Product/feature to monitor for impact]

**Quality Indicators:**
- [Metric to ensure quality maintained]

Step 5: Dashboard Assembly and Review Cadence (15 minutes)

Activities:

•Prioritize metrics (not all are equal)
•Organize into dashboard sections
•Define review cadence
•Set alert thresholds
•Assign ownership

Dashboard structure:

markdown

# [Product Name] Health Dashboard

## 🎯 North Star (Company-Level)
[1-2 company metrics this product impacts]

## 📊 Product North Star
[1-2 top-line product metrics]

## 🔄 Funnel Health

### Reach
- [Metric 1]: [Current value] [Trend ↑↓→]
- [Metric 2]: [Current value] [Trend ↑↓→]

### Activation
- [Metric 1]: [Current value] [Trend ↑↓→]
- Reach → Activation: [Conversion %]

### Engagement (Breadth)
- [Metric 1]: [Current value] [Trend ↑↓→]
- Activation → Engagement: [Conversion %]

### Engagement (Depth)
- [Metric 1]: [Current value] [Trend ↑↓→]

### Retention
- [Metric 1]: [Current value] [Trend ↑↓→]
- [Metric 2]: [Current value] [Trend ↑↓→]

## ⚠️ Counter-Metrics & Health Checks
- [Counter-metric 1]: [Current value] [Status: ✓ Healthy / ⚠️ Warning / 🚨 Alert]
- [Counter-metric 2]: [Current value] [Status: ✓ Healthy / ⚠️ Warning / 🚨 Alert]

## 📈 Key Insights (Updated Weekly)
- [Insight 1]
- [Insight 2]
- [Action items]

Review cadence definition:

markdown

## Dashboard Review Cadence

**Daily Review (5 minutes):**
- Audience: Product team
- Metrics: [2-3 most critical metrics]
- Purpose: Early problem detection
- Action threshold: [What triggers immediate investigation]

**Weekly Review (30 minutes):**
- Audience: Product team + stakeholders
- Metrics: Full dashboard
- Purpose: Trend analysis, prioritization
- Format: [Standup / Presentation / Async doc]

**Monthly Deep-Dive (60 minutes):**
- Audience: Product team + leadership
- Metrics: Full dashboard + segmentation analysis
- Purpose: Strategic review, goal setting
- Format: [Meeting / Written review]

**Quarterly Business Review:**
- Audience: Executives
- Metrics: North Star + key highlights
- Purpose: Alignment on strategy and resources

Alert thresholds:

markdown

## Alert Configuration

**Critical Alerts (Immediate attention):**
- [Metric] drops below [threshold]: [Who to notify]
- [Counter-metric] exceeds [threshold]: [Who to notify]

**Warning Alerts (Next-day review):**
- [Metric] trends down for [X days]: [Who to notify]

**Monitoring (Weekly review):**
- [Metric ranges to track]

Ownership:

markdown

## Metric Ownership

| Metric | Owner | Data Source | Update Frequency |
|--------|-------|-------------|------------------|
| [Metric 1] | [Name/Team] | [Tool/Table] | Real-time |
| [Metric 2] | [Name/Team] | [Tool/Table] | Daily |
| [Metric 3] | [Name/Team] | [Tool/Table] | Weekly |

Dashboard Design Principles

Principle 1: Comprehensive but Focused

Balance:

•Cover all lifecycle stages (comprehensive)
•Limit to 5-10 metrics total (focused)
•Prioritize metrics by impact and actionability

Avoid:

•Single-metric dashboards (miss problems elsewhere)
•20+ metric dashboards (overwhelming, unfocused)

Principle 2: Leading + Lagging Indicators

Leading indicators (early signals):

•Activation rate (predicts retention)
•Engagement frequency (predicts habit formation)
•NPS/satisfaction (predicts churn)

Lagging indicators (confirm outcomes):

•Retention rate (confirms product-market fit)
•Revenue (confirms monetization)
•Lifetime value (confirms unit economics)

Balance: Include both for complete picture

Principle 3: Volume + Quality

Volume metrics (quantity):

•Total users
•Total transactions
•Total content created

Quality metrics (value):

•User satisfaction scores
•Transaction value
•Content engagement rate

Balance: Prevent optimizing for wrong thing

Principle 4: Segment Where It Matters

Standard view:

•Aggregate metrics for whole product

Segmented views:

•By user type (power users, new users, paying users)
•By geography (if relevant)
•By cohort (when they joined)

When to segment:

•Behavior varies significantly by segment
•Different strategies for different segments
•Need to track specific initiatives

Common Mistakes

Mistake	Fix
Only measuring retention	Cover full funnel (reach through retention)
Vanity metrics without action	Ensure each metric is actionable by team
No counter-metrics	Add 2-3 to catch unintended effects
Too many metrics (20+)	Prioritize to 5-10 most important
No review cadence defined	Set daily/weekly/monthly schedule
Metrics without owners	Assign ownership for each
No alert thresholds	Define when to escalate

Success Criteria

Dashboard design succeeds when:

•Anchored to company North Star explicitly
•Covers all major lifecycle stages (4-5 stages)
•5-10 primary metrics with precise definitions
•2-3 counter-metrics included
•Review cadence established (daily, weekly, monthly)
•Alert thresholds defined
•Ownership assigned for each metric
•Stakeholders understand and accept dashboard
•Dashboard answers key product questions
•Team can explain why each metric matters

Real-World Example: Uber Driver Quality Dashboard

Step 1: North Star Anchoring (15 min)

code

Business Model: Two-sided marketplace
Company North Star: Monthly Active Drivers + Monthly Active Riders
Product (Driver Quality): Contributes to driver retention and rider satisfaction
"Healthy" = High-quality drivers staying active long-term
Strategic Priority: Quality + Retention (sustainable supply)

Step 2: Funnel Structure (20 min)

code

Reach: All active drivers (baseline)
  - Total active drivers (monthly)
  
Activation: Drivers engage with quality program
  - % viewing quality dashboard (target: 80%)
  - % reading quality tips (target: 50%)

Engagement (Breadth): Drivers aware of ratings
  - % checking ratings weekly (target: 60%)
  
Engagement (Depth): Drivers improve quality
  - Tips received per active driver
  - Rating improvement trend

Retention: Drivers maintain high quality
  - % drivers in 4.8+ bucket month-over-month
  - Hours driven by quality tier

Step 3: Proxy Metrics (20 min)

code

PRIMARY METRICS:

1. Driver Quality Distribution
   - Formula: Hours driven by rating bucket / Total hours
   - X-axis: 4.5-4.74, 4.75-5.0, 5.0+ with tips
   - Y-axis: Hours driven
   - Goal: Maximize hours in 5.0+ bucket

2. Quality Program Engagement
   - Formula: Drivers viewing dashboard weekly / Total active drivers
   - Target: 80%
   - Leading indicator of quality awareness

3. Tip Rate
   - Formula: Drivers receiving ≥1 tip per week / Total active drivers
   - Target: 40%
   - Quality indicator beyond ratings

4. Rating Stability
   - Formula: Drivers maintaining/improving rating MoM / Total
   - Target: 85%
   - Retention proxy

Step 4: Counter-Metrics (15 min)

code

COUNTER-METRICS:

1. Driver Churn Rate
   - What it catches: Quality standards too strict
   - Current: 8%/month
   - Acceptable: <10%
   - Alert if: >12%

2. Ride Acceptance Rate
   - What it catches: Drivers becoming too picky
   - Current: 92%
   - Acceptable: >85%
   - Alert if: <85%

3. Surge Pricing Frequency
   - What it catches: Insufficient supply
   - Current: 15% of rides
   - Acceptable: <20%
   - Alert if: >25%

Step 5: Dashboard Assembly (15 min)

code

# Uber Driver Quality Dashboard

## 🎯 Company North Star
- Monthly Active Drivers: 500K (↑ 2%)
- Hours Driven (Total): 8M (↑ 3%)

## 📊 Product North Star
- Hours Driven in 4.8+ Bucket: 4.8M / 60% of total (↑ 5%) [GOAL: 65%]
- Quality Program Engagement: 78% (↑ 3%)

## 🔄 Funnel Health

### Activation (Quality Program)
- Dashboard Views: 78% of drivers (target: 80%)
- Tips Read: 52% of drivers (target: 50%) ✓

### Engagement (Quality Awareness)
- Check Ratings Weekly: 58% (target: 60%)
- Tips Received: 38% of drivers (target: 40%)

### Retention (Quality Maintenance)
- Rating Stability MoM: 84% (target: 85%)
- Hours by Quality Tier:
  - 4.5-4.74: 1.5M / 19% (↓ 2%) [Good]
  - 4.75-5.0: 1.7M / 21% (→)
  - 5.0+ tips: 4.8M / 60% (↑ 5%) [Great]

## ⚠️ Counter-Metrics
- Driver Churn: 9.2%/month ✓ (threshold: <10%)
- Acceptance Rate: 90% ✓ (threshold: >85%)
- Surge Frequency: 17% ✓ (threshold: <20%)

## 📈 Key Insights (Week of Dec 1)
- Strong progress toward 65% quality goal (on track for Q1)
- Tip rate slightly below target; testing new prompts
- Churn elevated but within acceptable range
- Action: Launch tip prompt experiment next week

---

## Review Cadence

**Daily (5 min):** Churn rate, acceptance rate (critical alerts)
**Weekly (30 min):** Full dashboard, trend review
**Monthly (60 min):** Deep-dive, segmentation analysis
**Quarterly:** Strategic review with leadership

## Alert Configuration

**Critical:**
- Churn >12%: Alert product lead + ops
- Acceptance <85%: Alert product lead + ops

**Warning:**
- Quality goal progress <2%/month: Weekly review
- Counter-metric approaching threshold: Flag in review

Time to complete: 90 minutes

Related Skills

This workflow orchestrates these skills:

•north-star-alignment (Step 1)
•funnel-metric-mapping (Step 2)
•proxy-metric-selection (Step 3)
•tradeoff-evaluation (Step 4)

Related Workflows

•metrics-definition: Similar process but for one-time metric selection
•goal-setting: Uses dashboard metrics to set OKR targets
•tradeoff-decision: Uses dashboard to monitor trade-offs

Time Estimate

Total: 85-100 minutes

•Step 1 (North Star): 15 min
•Step 2 (Funnel): 20 min
•Step 3 (Proxy): 20 min
•Step 4 (Counter-metrics): 15 min
•Step 5 (Assembly): 15 min
•Buffer: 10 min