| name | developer-churn |
| description | When the user wants to understand, reduce, or recover from developer churn. Trigger phrases include "why developers leave," "churn rate," "win-back campaign," "at-risk users," "developer retention," " |
| category | Document Processing |
| source | antigravity |
| tags | ["react","api","ai","agent","workflow","document","security","stripe","marketing"] |
| url | https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/developer-churn |
Developer Churn
When to Use
Use this skill when you need when the user wants to understand, reduce, or recover from developer churn. Trigger phrases include "why developers leave," "churn rate," "win-back campaign," "at-risk users," "developer retention," "preventing churn," or "competitor switching.".
This skill helps you understand why developers leave, identify at-risk users before they churn, and win back those who've already left. No guilt trips or desperate discounts — just honest understanding and genuine value.
Before You Start
-
Load your developer audience context:
- Check if
.agents/developer-audience-context.md exists
- If not, run the
developer-audience-context skill first
- Understanding your developers' alternatives and pain points is critical for churn analysis
-
Gather your data:
- Current churn rate by segment
- Most recent churned users (last 30-90 days)
- Support ticket history for churned users
- Usage patterns before churn
- Exit survey data (if any)
Understanding Developer Churn
Developer churn is different from typical SaaS churn:
| Consumer/SMB SaaS | Developer Tools |
|---|
| Price sensitivity high | Value sensitivity high |
| Features drive decisions | DX drives decisions |
| Support tickets = engagement | Support tickets = friction |
| Monthly churn cycles | Project-based churn |
| Competitor marketing works | Peer recommendations work |
Key insight: Developers don't leave because of price. They leave because of friction, frustration, or finding something better.
The 6 Reasons Developers Churn
1. Developer Experience (DX) Issues
Symptoms:
- High time-to-first-value
- Frequent support tickets on basic tasks
- Complaints about docs or SDKs
- "It's too complicated" feedback
Root causes:
- Poor documentation
- Buggy SDKs
- Breaking changes without migration paths
- Confusing authentication
- Missing quickstarts
Detection signals:
- Support tickets mentioning "confused" or "doesn't work"
- High signup-to-activation drop-off
- Long time between signup and first API call
- Multiple failed API calls before success
2. Pricing and Billing Friction
Symptoms:
- Downgrades before cancellation
- Usage dropping to stay under limits
- Questions about billing
- Requests for enterprise/custom pricing
Root causes:
- Unpredictable costs
- Expensive for early-stage
- No free tier or too restrictive
- Poor price-to-value perception
- Billing surprises
Detection signals:
- Sudden usage reduction after billing cycle
- Pricing page visits from logged-in users
- Support tickets about unexpected charges
- API calls stopping mid-month
3. Superior Alternatives
Symptoms:
- Sudden churn (not gradual)
- Multiple team members churning together
- Churning without complaints
- "We're going a different direction"
Root causes:
- Competitor launched better feature
- Open source alternative matured
- Bigger player entered your space
- Their stack changed (new language/framework)
Detection signals:
- Sudden stop in usage (no gradual decline)
- Competitor mentions in support/feedback
- Traffic to your docs from competitor domains
- Social mentions comparing you to alternatives
4. Project Death
Symptoms:
- Gradual decline to zero
- No support contact
- Ignores all communication
- Whole company churn
Root causes:
- Their project was cancelled
- Startup failed
- Prototype never went to production
- Budget cuts
Reality check: You can't prevent this. Don't waste energy trying.
Detection signals:
- Slow decline over weeks/months
- No login activity
- No response to any outreach
- Domain no longer resolves
5. Integration Failure
Symptoms:
- High engagement then sudden stop
- Technical support tickets unresolved
- "Doesn't work with X" feedback
- Stuck at implementation phase
Root causes:
- Your product doesn't fit their stack
- Missing integration they need
- Technical limitation they hit
- SDK doesn't support their use case
Detection signals:
- Lots of docs page views on specific integration
- Support tickets about specific tech stack
- API calls from testing environment only
- "Evaluation" mentioned in communications
6. Involuntary Churn
Symptoms:
- Churn after failed payment
- No other warning signs
- Often surprised when contacted
Root causes:
- Expired credit card
- Card fraud protection
- Changed payment method
- Forgot to update billing
Detection signals:
- Failed payment events
- Usage continues until hard cutoff
- Quick reactivation when contacted
Identifying At-Risk Developers
Engagement Scoring
Create a simple health score:
| Signal | Weight | Calculation |
|---|
| API calls | 30% | This week vs last 4 week avg |
| Login frequency | 20% | Days since last login |
| Feature adoption | 20% | |
