563 lines
11 KiB
Markdown
563 lines
11 KiB
Markdown
# Developer Product Metrics
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Comprehensive guide to measuring success for technical products, developer tools, and APIs.
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---
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## Why Developer Metrics Are Different
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Developer products have unique characteristics:
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- **High technical barriers** to adoption
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- **Longer evaluation** periods
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- **Community-driven** growth
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- **Usage-based** pricing models
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- **Quality over quantity** (one great developer > 100 casual users)
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Traditional B2B SaaS metrics don't always apply directly.
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---
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## The Developer Funnel
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```
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Awareness → Interest → Evaluation → Activation → Engagement → Retention → Monetization
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```
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Each stage has specific metrics.
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---
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## 1. Awareness Metrics
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### Top-of-Funnel
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**Website Traffic:**
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- Documentation page views
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- Landing page visits
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- Blog traffic
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- GitHub repository views
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**Search & Discovery:**
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- Organic search rankings (for key terms)
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- GitHub stars
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- Stack Overflow mentions
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- Social media mentions
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**Community Presence:**
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- Discord/Slack members
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- Reddit subscribers
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- Newsletter subscribers
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- Conference attendance
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**Targets (vary by company):**
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- 50K monthly docs views (early stage)
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- 500K monthly docs views (growth stage)
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- 1K+ GitHub stars (open source component)
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---
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## 2. Interest Metrics
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### Consideration Stage
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**Engagement:**
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- Time on documentation
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- Pages per session
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- Video views (tutorials)
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- GitHub README views
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**Content Consumption:**
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- Blog post reads
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- Tutorial completion rate
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- Demo video watch time
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- Webinar registrations
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**Social Proof:**
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- Case study views
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- Customer testimonials read
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- Comparison page visits
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**Targets:**
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- 5+ minute average session duration
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- 4+ pages per session
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- 50%+ video completion rate
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---
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## 3. Evaluation Metrics
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### Trial/Sandbox Stage
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**Sign-Up:**
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- Developer sign-ups
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- API key requests
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- Sandbox activations
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- Free tier activations
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**Time to Value:**
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- **Time to first API call** (target: < 10 minutes)
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- **Time to "Hello World"** (target: < 15 minutes)
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- **Time to integration** (target: < 1 hour)
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**Documentation Engagement:**
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- Getting started guide views
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- Code sample copies
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- SDK downloads
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- Postman collection imports
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**Targets:**
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- 1K+ sign-ups per month (early stage)
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- 60% make first API call within 24 hours
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- 10 minutes median time to first call
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---
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## 4. Activation Metrics
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### First Value Realized
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**Critical Activation Events:**
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- **First successful API call**
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- **First integration deployed**
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- **First production request**
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- **SDK installed and used**
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- **Sandbox → production migration**
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**Activation Rate:**
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```
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Activation Rate = (Users who complete activation event) / (Total sign-ups)
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```
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**Depth of Activation:**
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- Features explored
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- Endpoints called
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- SDKs used
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- Integrations enabled
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**Targets:**
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- 50-70% activation rate (first API call)
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- 30-40% activation rate (production deployment)
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- 80%+ complete getting started guide
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---
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## 5. Engagement Metrics
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### Active Usage
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**Daily/Weekly/Monthly Active Developers (DAD/WAD/MAD):**
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```
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DAD = Unique developers making API calls daily
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WAD = Unique developers active weekly
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MAD = Unique developers active monthly
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```
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**Stickiness:**
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```
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Stickiness = DAD / MAD
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```
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- Target: > 20% (good)
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- Target: > 40% (excellent)
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**API Usage:**
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- **Total API calls** per day/week/month
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- **API calls per developer**
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- **Endpoints used** per developer
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- **Error rate** (target: < 1%)
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**Feature Adoption:**
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- % of developers using key features
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- Time to feature adoption
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- Feature depth (how many features per user)
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**Targets:**
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- 40%+ stickiness (DAD/MAD)
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- 1K+ API calls per active developer per month
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- < 1% error rate
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- 3+ features adopted per developer
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---
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## 6. Retention Metrics
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### Developer Retention
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**Cohort Retention:**
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```
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Day 1 Retention = Developers active on Day 1 / Total sign-ups
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Day 7 Retention = Developers active on Day 7 / Total sign-ups
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Day 30 Retention = Developers active on Day 30 / Total sign-ups
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```
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**Typical Developer Product Retention:**
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- Day 1: 60-70%
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- Day 7: 30-50%
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- Day 30: 20-40%
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- Day 90: 15-30%
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**Why Developer Retention Is Lower:**
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- Evaluation period (many are just testing)
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- Project-based usage (finish project, stop using)
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- This is normal and expected
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**Churn Rate:**
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```
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Monthly Churn = Developers who stopped using / Active developers at month start
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```
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**Resurrection Rate:**
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```
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Resurrection = Churned developers who return / Total churned developers
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```
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**Targets:**
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- < 5% monthly churn (paid users)
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- 40%+ Day 7 retention
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- 25%+ Day 30 retention
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---
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## 7. Monetization Metrics
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### Revenue Metrics
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**Conversion Metrics:**
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```
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Free → Paid Conversion Rate = Paid users / Total active users
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```
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- Target: 3-10% (varies widely by product)
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**Revenue Metrics:**
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- **MRR** (Monthly Recurring Revenue)
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- **ARR** (Annual Recurring Revenue)
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- **ARPU** (Average Revenue Per User)
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- **Net Revenue Retention** (NRR)
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**Usage-Based Pricing Metrics:**
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- **Average API calls per paid user**
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- **Tier distribution** (how many in each pricing tier)
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- **Upgrade rate** (free → paid, basic → pro)
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- **Expansion revenue** (existing customers spending more)
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**Targets:**
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- 5%+ free-to-paid conversion
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- 110%+ Net Revenue Retention
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- $50-$500 ARPU (varies by product)
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---
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## Developer-Specific Metrics
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### Code Quality Metrics
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**SDK Quality:**
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- **Downloads** per month
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- **GitHub stars**
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- **Issues opened** vs. closed
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- **PR acceptance** rate
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- **Time to resolve** issues
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**Documentation Quality:**
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- **Search success** rate (did they find what they needed?)
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- **Time on page** (too short = unclear, too long = can't find)
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- **Bounce rate** on docs
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- **Feedback** (thumbs up/down on docs pages)
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**Targets:**
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- 90%+ search success rate
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- < 40% bounce rate on docs
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- 80%+ positive feedback on docs
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---
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### Developer Experience Metrics
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**Time-Based:**
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- Time to first API call
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- Time to production
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- Time to integrate
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- Time to debug
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**Friction Points:**
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- Authentication failures
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- API errors
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- SDK install issues
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- Documentation gaps
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**Support Metrics:**
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- Support tickets per MAD
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- Time to first response
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- Time to resolution
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- Community forum response time
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**Targets:**
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- < 5 minutes to first API call
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- < 1 support ticket per 100 MAD
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- < 4 hours first response time
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- 90%+ questions answered by community
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---
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## Developer Satisfaction
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### Net Promoter Score (NPS)
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Survey question: "How likely are you to recommend [product] to other developers?"
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**Scale:** 0-10
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**Calculation:**
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```
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NPS = % Promoters (9-10) - % Detractors (0-6)
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```
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**Developer Product Benchmarks:**
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- **Excellent:** NPS > 50
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- **Good:** NPS 30-50
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- **Needs Work:** NPS < 30
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### Developer Sentiment
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**Qualitative Indicators:**
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- Social media sentiment
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- Community forum tone
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- GitHub issue sentiment
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- Review site ratings (G2, Capterra)
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- Stack Overflow sentiment
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**Quantitative Tracking:**
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- Positive vs. negative mentions
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- Sentiment score (automated analysis)
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- Review ratings (1-5 stars)
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---
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## Launch-Specific Metrics
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### Launch Day Metrics
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**Day 1:**
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- Sign-ups / API keys
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- First API calls
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- Documentation views
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- Blog post views
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- Social media impressions
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- Email open rate
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- Email click rate
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**Targets (Tier 1 launch):**
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- 5K+ sign-ups
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- 50%+ activation rate (first call)
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- 100K+ docs views
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- 50K+ blog views
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---
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### Week 1 Metrics
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- Total sign-ups
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- Day 7 retention rate
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- Active developers
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- API calls made
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- Support tickets
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- Community questions
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- Social mentions
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**Targets (Tier 1):**
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- 10K+ total sign-ups
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- 40%+ Day 7 retention
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- 5K+ active developers
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- 1M+ API calls
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- < 50 support tickets
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---
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### Month 1 Metrics
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- Monthly Active Developers (MAD)
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- Free → paid conversion
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- NPS score
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- Documentation coverage (no major gaps)
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- Community health
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- Feature adoption
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**Targets (Tier 1):**
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- 25K+ MAD
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- 3-5% paid conversion
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- NPS > 40
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- 80%+ positive doc feedback
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---
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## Metrics Dashboard Template
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### Executive Dashboard
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**Adoption:**
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- Total Developers: [X]
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- MAD: [X]
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- Growth Rate: [X%]
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**Engagement:**
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- DAD/MAD: [X%]
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- API Calls/Day: [X]
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- Error Rate: [X%]
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**Retention:**
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- Day 7: [X%]
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- Day 30: [X%]
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- Churn: [X%]
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**Revenue:**
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- MRR: $[X]
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- ARPU: $[X]
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- NRR: [X%]
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**Quality:**
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- NPS: [X]
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- Support Tickets/MAD: [X]
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---
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### Product Team Dashboard
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**This Week:**
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- New Developers: [X]
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- Activation Rate: [X%]
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- Features Adopted: [X]
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- Top API Endpoints: [List]
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**Trends:**
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- MAD (7-day trend): [Graph]
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- API Calls (7-day): [Graph]
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- Error Rate (7-day): [Graph]
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**Health:**
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- Documentation Gaps: [Count]
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- Open Issues: [Count]
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- P0 Bugs: [Count]
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---
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## Metric Collection
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### Where to Track
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**Product Analytics:**
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- Amplitude
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- Mixpanel
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- Heap
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- PostHog
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**API Analytics:**
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- Moesif
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- API metrics (custom)
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- CloudWatch / Datadog
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**Documentation Analytics:**
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- Google Analytics
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- Readme.io analytics
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- GitBook analytics
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**Developer Feedback:**
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- Intercom
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- Zendesk
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- Community forum analytics
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- Survey tools (Delighted, SurveyMonkey)
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---
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## Setting Targets
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### Early Stage (0-1 year)
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Focus on **activation** and **engagement**:
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- Sign-ups: 1K-10K/month
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- Activation: 50%+
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- MAD: 500-5K
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- Day 7 Retention: 30%+
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### Growth Stage (1-3 years)
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Focus on **scale** and **retention**:
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- Sign-ups: 10K-50K/month
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- MAD: 10K-100K
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- Day 30 Retention: 25%+
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- Free→Paid: 5%+
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### Mature Stage (3+ years)
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Focus on **efficiency** and **expansion**:
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- MAD: 100K+
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- NRR: 110%+
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- ARPU: Increasing
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- CAC Payback: < 12 months
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---
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## Common Pitfalls
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### Vanity Metrics
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**Avoid:**
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- Total registered users (most are inactive)
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- Total API calls (could be from one user)
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- GitHub stars alone (may not use product)
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**Focus on:**
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- Active users (making API calls)
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- Retained users (coming back)
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- Engaged users (using multiple features)
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### Wrong Benchmarks
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Don't compare developer product metrics to:
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- B2C social apps (much higher DAU/MAU)
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- Enterprise SaaS (lower volume, higher ACV)
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- E-commerce (transactional, not sustained use)
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Use developer product benchmarks instead.
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---
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## Summary: Key Metrics to Track
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**Must Track:**
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1. Monthly Active Developers (MAD)
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2. Activation Rate (first API call)
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3. Day 7 & Day 30 Retention
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4. Stickiness (DAD/MAD)
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5. API Error Rate
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6. NPS
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**Should Track:**
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7. Free → Paid Conversion
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8. Time to First API Call
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9. Documentation Effectiveness
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10. Support Ticket Volume
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**Nice to Have:**
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11. GitHub Stars/Activity
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12. Community Engagement
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13. Social Sentiment
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14. Feature Adoption Depth
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Start with the must-track metrics, then expand.
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---
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## Developer Metric Formulas
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Quick reference:
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```
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Activation Rate = Activated Users / Sign-ups
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Stickiness = DAD / MAD
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Churn Rate = Users Lost / Total Users
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NRR = (MRR + Expansion - Churn) / Starting MRR
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LTV = ARPU / Churn Rate
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CAC Payback = CAC / (ARPU * Gross Margin)
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```
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**Remember:** Metrics should drive action, not just reporting. If a metric doesn't change behavior, don't track it.
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