dvcrn Quick Reference
| Topic | File |
|---|---|
| Monetization models & paywall design | monetization.md |
| Unit economics (CAC, LTV, payback) | economics.md |
| Growth loops & acquisition channels | growth.md |
| Retention benchmarks by category | benchmarks.md |
Core Framework
Stage-Aware Priorities
| Stage | Focus | Key Metric |
|---|---|---|
| Pre-PMF | Activation + Retention | D7 retention > 20% |
| Post-PMF | Acquisition + Conversion | CAC payback < 6 months |
| Scaling | LTV optimization + Loops | LTV:CAC > 3:1 |
The 30-Second Rule
Consumer products win or lose in the first 30 seconds:
- Is there a hook? (emotional trigger, curiosity, benefit)
- How many taps to value? (target: ≤3)
- Is signup deferred until after value shown?
Critical Metrics
- Activation: % reaching "aha moment" in first session
- Retention: D1/D7/D30 by acquisition cohort
- Monetization: Conversion rate, ARPU, payback period
- Referral: Viral coefficient (K-factor), organic vs paid ratio
Anti-Patterns (Common B2C Mistakes)
- Building for power users — The 80% casual users pay the bills
- Generous freemium — If free tier solves the problem, why upgrade?
- Vanity metrics — MAU without defining "active" hides churn
- B2B thinking — Long onboarding, feature demos, rational appeals
- Ignoring emotions — Status, FOMO, delight drive consumer behavior
- Late paywall — Users habituate to free before seeing upgrade value
Decision Support
For any B2C decision, apply this framework:
- Validate demand first — Search Reddit/Twitter/forums for complaints about the problem
- Design monetization early — Model matters more than price initially
- Define activation moment — What must happen for user to "get it"?
- Plan growth loop — Paid-only doesn't scale; what compounds?
- Set kill metrics — Below what retention do you pivot?