Business: 
Current metrics: 
Problem: 

Build measurement system:

1. Hierarchy of metrics
   Tier 1 (North Star): One metric that defines success
   - Revenue? Users? Engagement? Impact?
   - For SaaS: Usually ARR (annual recurring revenue)
   - For marketplace: Usually GMV (gross merchandise volume)
   - For platform: Usually DAU (daily active users)
   
   Tier 2 (Key metrics): 5-7 metrics that drive north star
   - Acquisition: How many new customers/users?
   - Engagement: Are they using?
   - Monetization: Are they paying?
   - Retention: Do they stay?
   - Expansion: Do they grow with you?
   
   Tier 3 (Operational): 20+ metrics that track execution
   - Customer acquisition cost (CAC)
   - Customer lifetime value (LTV)
   - Churn rate
   - Net revenue retention (NRR)
   - Sales cycle length
   - etc.

2. The trap: Vanity metrics
   What NOT to obsess over:
   - Total signups (who cares, track conversions)
   - Page views (who cares, track engagement)
   - Total users ever (who cares, track active users)
   - Revenue (who cares, track recurring revenue and retention)
   
   These go up but don't mean business is healthy.

3. Leading vs lagging indicators
   Lagging: Outcome you want but can't control in real-time
   - Churn (happens over time)
   - Revenue (accumulates)
   - Customer lifetime value (takes months/years)
   
   Leading: Early signals that predict outcomes
   - Product usage (predicts retention)
   - NPS (predicts churn)
   - Time-to-first-value (predicts retention)
   - Expansion usage (predicts NRR)
   
   Track leading indicators to predict before lagging

4. Metrics by function
   Product:
   - Feature adoption rate
   - Session length
   - Task completion rate
   
   Sales:
   - CAC by channel
   - Sales cycle length
   - Win rate vs competition
   
   Marketing:
   - Lead volume
   - Marketing-influenced revenue
   - CAC vs LTV ratio
   
   Customer Success:
   - NRR
   - Churn rate
   - Customer health score

5. Cohort analysis
   Don't just track totals. Track cohorts:
   - Customers from March have 40% retention
   - Customers from April have 45% retention
   - Why different? What changed?
   
   This reveals what's working.

6. Benchmarking
   How do you compare?
   - What's industry average for your metric?
   - Where are you vs average?
   - Who's winning? What are they doing?
   - What's good, what's OK, what's bad?

7. Measurement discipline
   For each key metric:
   - Definition: Exactly how is it calculated?
   - Owner: Who tracks this?
   - Cadence: Daily? Weekly? Monthly?
   - Target: What are you trying to achieve?
   - Actionable: If metric moves, what do you DO?
   
   If you can't answer all 5, you're wasting time tracking it.

8. Dashboard
   What does your executive dashboard show?
   - Top-left: North star (the one metric that matters)
   - Next 4: Key drivers of north star
   - Bottom section: Operational metrics
   - Trend: Is it going up/down/flat?
   
   Anything else is noise.

Examples

Input

{
  "business": "B2B SaaS (AI monitoring platform)",
  "currentMetrics": "Total signups, MRR, customer count, page views, signup rate",
  "mainProblem": "We're growing MRR but churn is increasing - is business actually healthy?"
}

Output

Complete measurement framework with metric hierarchy, vanity metric identification, leading vs lagging indicators, function-specific metrics, cohort analysis approach, benchmarking strategy, measurement discipline, and executive dashboard design.

Sources

https://www.amazon.com/Lean-Analytics-Everything-Metrics-Startup/dp/1449335675

Ready to explore more prompts?

Discover our complete library of research-backed prompts with proven results. From multi-expert panels to tree-of-thought reasoning.

Browse All Prompts Learn Prompt Engineering