Chapter 5: Metrics & Success Criteria
North Star Metric, Retention, NPS, and actionable analytics.
What Gets Measured Gets Managed
Startups drown in data. Every analytics tool offers hundreds of metrics—downloads, page views, sessions, sign-ups. The problem isn't lack of data; it's knowing which data actually matters.
The wrong metrics create a dangerous illusion of progress. The right metrics force honest confrontation with reality.
The Core Insight
There's only one metric that proves product-market fit: retention. If users don't come back, nothing else matters. Build your entire measurement strategy around understanding and improving retention.
Bug #1: Celebrating Vanity Metrics
Vanity metrics are the most dangerous trap in startup analytics. They always go up over time, making the team feel good—while the business slowly dies.
The Bug
"We hit 100,000 downloads!"
Cumulative metrics only go up. A product can have 100K downloads and 0 active users. These metrics create false confidence while your actual business hemorrhages.
The Fix
Focus exclusively on actionable metrics.
Track cohort retention, activation rate, and conversion rate—metrics that can go down, that tell you something is broken, and that you can directly influence.
Vanity vs. Actionable Metrics
Vanity Metrics
These lie. They only go up. They feel good but teach nothing.
| Cumulative downloads |
| Total registered users |
| Total page views |
| Social media followers |
| "Time on site" without context |
Actionable Metrics
These tell the truth. They can go down. They drive action.
| Cohort retention (Week 1, Week 4, Week 8) |
| Activation rate (% who reach "aha moment") |
| Conversion rate (Visitor → Trial → Paid) |
| Net Promoter Score (NPS) |
| Revenue per user (RPU) |
The Vanity Test
Ask yourself: "Can this metric go down?" If a metric can only increase over time (like cumulative downloads), it's vanity. If it can decrease and signal something is broken (like Day 30 retention), it's actionable.
The North Star Metric (NSM)
Your North Star Metric is the single number that best captures the core value your product delivers. It aligns the entire organization—product, marketing, sales, support—around one goal.
Criteria for a Good North Star Metric
| Value-Based | Reflects value delivered to customers, not just revenue extracted |
| Leading Indicator | Predicts future success (revenue is a lagging indicator) |
| Actionable | The team can directly influence it through product decisions |
| Understandable | Every team member can explain what it means |
North Star Examples by Category
Consumption Products
Spotify: Time Spent Listening
Netflix: Watch Time
YouTube: Watch Minutes
Transaction Products
Airbnb: Nights Booked
Uber: Rides per Week
Amazon: Purchases per Month
Productivity Products
Slack: Messages Sent
Zoom: Hosted Meetings
Notion: Blocks Created
Finding Your North Star
Answer this: "What single action, when done repeatedly, indicates the customer is getting value?" That action is your North Star. For Airbnb, it's booking nights. For Spotify, it's listening to music. For Slack, it's sending messages.
Retention: The Only Metric That Matters
For an early-stage MVP, retention is the only metric that truly proves product-market fit. If users don't come back, you haven't built something people want.
The Bug
"Let's focus on acquisition. We need more users."
Acquisition without retention is burning cash into a leaky bucket. You're paying to acquire users who immediately leave. Fix retention before scaling acquisition.
The Fix
Build a retention curve first.
Track cohort retention over time. Your curve should flatten (users stick around), not plummet to zero. Don't scale until the curve flattens.
Retention Benchmarks by Business Model
What "Good" Looks Like
| Business Model | Metric | Weak | Good | Great |
|---|---|---|---|---|
| B2B SaaS | Net Revenue Retention | <90% | 100-110% | >120% |
| Monthly Logo Churn | >5% | 2-3% | <2% | |
| B2C Mobile | Day 1 Retention | <25% | 30-40% | >50% |
| Day 30 Retention | <10% | 15-20% | >25% | |
| Consumer Web | Week 1 Retention | <15% | 20-30% | >40% |
| Month 3 Retention | <10% | 15-25% | >30% |
The Retention Curve
Reading Your Retention Curve
Plot the percentage of users still active over time. What you're looking for:
| Curve goes to zero | You don't have product-market fit. Users try and leave. Fix the product. |
| Curve flattens low | You have a niche audience. Consider if the segment is big enough. |
| Curve flattens high | Product-market fit achieved. You can now scale acquisition. |
Net Promoter Score (NPS)
NPS measures customer loyalty and predicts viral growth. It's simple, standardized, and benchmarkable.
How NPS Works
The Question: "On a scale of 0-10, how likely are you to recommend [Product] to a friend or colleague?"
Promoters (9-10)
Active advocates. Will refer others.
Passives (7-8)
Satisfied but unenthusiastic. Won't refer.
Detractors (0-6)
Unhappy. May actively discourage others.
Formula: NPS = % Promoters - % Detractors (ranges from -100 to +100)
NPS Benchmarks
Below 0
Danger zone. More detractors than promoters. Fix immediately.
0-30
Good. More lovers than haters. Room to improve.
30-50
Great. Typical for successful SaaS companies.
50+
World-class. Apple, Tesla territory. Strong viral potential.
The Real Value of NPS
The number matters less than the follow-up question: "Why did you give that score?" The qualitative feedback reveals what's broken (from detractors) and what's magical (from promoters).
Your Metrics Dashboard Checklist
The MVP Metrics Stack
| North Star defined: One metric that captures core value delivery | |
| Retention tracked: Cohort retention by week (D1, D7, D30 minimum) | |
| Activation defined: Clear "aha moment" and % of users reaching it | |
| NPS measured: Score + qualitative feedback collection | |
| Vanity eliminated: No cumulative metrics in weekly reviews |
Key Takeaways
Remember These Truths
- Vanity metrics lie. If a metric can only go up, it's hiding the truth.
- Define your North Star. One metric that captures the core value you deliver.
- Retention is everything. If users don't come back, nothing else matters.
- Flatten the curve first. Don't scale acquisition until retention stabilizes.
- NPS reveals why. The qualitative follow-up is more valuable than the score.
Now that you know what to measure, let's explore how to prepare for launch and manage beta testing effectively.
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Start Free TodayWorks Cited & Recommended Reading
RAT vs MVP Philosophy
- 1. Ries, E. (2011). The Lean Startup. Crown Business.
- 2. "Why RAT (Riskiest Assumption Test) beats MVP every time." LinkedIn
- 3. "Pretotyping: The Art of Innovation." Pretotyping.org
- 6. "Continuous Discovery: Product Trio." Product Talk
- 7. "MVP Fidelity Spectrum Guide." SVPG
Minimum Lovable Product
- 8. Olsen, D. (2015). The Lean Product Playbook. Wiley.
- 9. "From MVP to MLP: Why 'Viable' Is No Longer Enough." First Round Review
- 10. "Minimum Lovable Product framework." Amplitude Blog
Hypothesis-Driven Development
- 11. Gothelf, J. & Seiden, J. (2021). Lean UX. O'Reilly Media.
- 12. "Hypothesis-Driven Development in Practice." ThoughtWorks Insights
- 13. "Experiment Tracking Best Practices." Optimizely
- 14. "Build-Measure-Learn: The Scientific Method for Startups." Harvard Business Review
Assumption Mapping
- 15. Bland, D. & Osterwalder, A. (2019). Testing Business Ideas. Wiley.
- 16. "Risk vs. Knowledge Matrix." Miro Templates
- 17. "Identifying Riskiest Assumptions." Intercom Blog
User Story & Impact Mapping
- 20. Patton, J. (2014). User Story Mapping. O'Reilly Media.
- 21. Adzic, G. (2012). Impact Mapping. Provoking Thoughts.
- 22. "Jobs-to-Be-Done Story Framework." JTBD.info
- 23. "The INVEST Criteria for User Stories." Agile Alliance
- 24. "North Star Metric Framework." Amplitude
- 25. "Opportunity Solution Trees." Product Talk
- 26. Torres, T. (2021). Continuous Discovery Habits. Product Talk LLC.
Pretotyping Techniques
- 27. Savoia, A. (2019). The Right It. HarperOne.
- 28. "Fake Door Testing Guide." UserTesting
- 29. "Wizard of Oz Testing Method." Nielsen Norman Group
- 30. "Concierge MVP Explained." Grasshopper
Prioritization Frameworks
- 31. "ICE Scoring Model." ProductPlan
- 32. "RICE Prioritization Framework." Intercom
- 33. "Kano Model for Feature Analysis." Folding Burritos
- 34. "MoSCoW Method Guide." ProductPlan
Build vs Buy & No-Code
- 35. "No-Code MVP Tools Landscape." Makerpad
- 37. "Technical Debt in Early Startups." a16z
- 38. "Prototype Fidelity Selection." Interaction Design Foundation
- 39. "API-First Development Strategy." Swagger
- 40. "Rapid Prototyping with Bubble & Webflow." Bubble Blog
Metrics & Analytics
- 41. Croll, A. & Yoskovitz, B. (2013). Lean Analytics. O'Reilly.
- 42. "One Metric That Matters (OMTM)." Lean Analytics
- 43. McClure, D. "Pirate Metrics (AARRR)." 500 Startups
- 44. "Vanity Metrics vs. Actionable Metrics." Mixpanel
- 45. "Cohort Analysis Deep Dive." Amplitude
- 46. "A/B Testing Statistical Significance." Optimizely
- 47. "Product Analytics Instrumentation." Segment Academy
- 48. "Activation Metrics Framework." Reforge
- 49. "Leading vs Lagging Indicators." Productboard
- 50. "Retention Curve Analysis." Sequoia Capital
- 51. "Feature Adoption Tracking." Pendo
- 52. "Experimentation Velocity Metrics." ExP Platform
Launch Operations & Analysis
- 53. "Soft Launch Strategy." Mind the Product
- 54. "Feature Flag Best Practices." LaunchDarkly
- 55. "Beta Testing Program Design." BetaList
- 56. "Customer Feedback Loop Systems." Canny
- 57. "Rollback Strategy Planning." Atlassian
- 58. "Why Startups Fail: Post-Mortems." CB Insights
- 59. "Pivot vs Persevere Decisions." Steve Blank
- 60. "Learning from Failed Experiments." HBR Innovation
This playbook synthesizes methodologies from Lean Startup, Design Thinking, Jobs-to-Be-Done, Pretotyping, and modern product management practices. References are provided for deeper exploration of each topic.