Success Metrics & KPI Framework
- Market Validation: 8/10
- Technical Feasibility: 9/10
- Competitive Advantage: 7/10
- Business Viability: 9/10
- Execution Clarity: 8/10
Success Metrics Dashboard
A. Product & Technical Metrics
| Metric | Definition | Target (Month 3) | Target (Month 6) | Target (Month 12) | How to Measure |
|---|---|---|---|---|---|
| Uptime | % time product is available | 99% | 99.5% | 99.9% | Monitoring tools (Uptime Robot) |
| Page Load Time | Avg time to interactive | <3s | <2s | <1.5s | Web Vitals, Lighthouse |
| API Response Time | P95 latency | <500ms | <300ms | <200ms | API monitoring |
| Error Rate | % of requests with errors | <2% | <1% | <0.5% | Sentry, logging |
| Feature Adoption | % users using new features | 40% | 55% | 70% | Analytics |
B. User Engagement & Retention Metrics
| Metric | Definition | Target (Month 3) | Target (Month 6) | Target (Month 12) | How to Measure |
|---|---|---|---|---|---|
| Daily Active Users (DAU) | Unique users per day | 50 | 150 | 500 | Analytics |
| Monthly Active Users (MAU) | Unique users per month | 300 | 800 | 2,500 | Analytics |
| D30 Retention | Users returning Day 30 | 15% | 30% | 40% | Cohort analysis |
| Net Promoter Score (NPS) | Willingness to recommend | 20 | 35 | 50 | Survey |
C. Growth & Acquisition Metrics
| Metric | Definition | Target (Month 3) | Target (Month 6) | Target (Month 12) | How to Measure |
|---|---|---|---|---|---|
| New Signups | New users per month | 100 | 300 | 800 | Analytics |
| Traffic Sources | Top 3 channels | Organic (40%), Paid (30%), Referral (30%) | - | - | Analytics |
| CAC Payback Period | Months to recover CAC | 3 mo | 2 mo | 1 mo | LTV/CAC calc |
D. Revenue & Financial Metrics
| Metric | Definition | Target (Month 3) | Target (Month 6) | Target (Month 12) | How to Measure |
|---|---|---|---|---|---|
| Monthly Recurring Revenue (MRR) | Predictable monthly revenue | $500 | $3,000 | $15,000 | Stripe dashboard |
| Customer Acquisition Cost (CAC) | Cost to acquire 1 customer | $100 | $80 | $60 | Marketing spend / new customers |
| Customer Lifetime Value (LTV) | Total revenue per customer | $600 | $900 | $1,200 | LTV formula |
E. Business Health & Operational Metrics
| Metric | Definition | Target (Month 3) | Target (Month 6) | Target (Month 12) | How to Measure |
|---|---|---|---|---|---|
| Monthly Churn Rate | % customers who cancel/mo | 8% | 6% | 4% | Cancellations / total customers |
| Net Revenue Retention | Expansion - churn | 90% | 100% | 110% | (MRR + expansion - churn) / starting MRR |
| Support Tickets | Tickets per 100 users/mo | 15 | 10 | 8 | Support system |
Comprehensive Risk Register
Severity: 🔴 High | Likelihood: Medium (40%)
Description: Users sign up but don't engage. Retention falls below 20% D30. Core value proposition doesn't resonate, and competitors offer better alternatives. Market timing is off (too early/late).
Mitigation Strategies: Conduct 30+ customer interviews in Weeks 1-4. Build landing page waitlist (target minimum 300 signups before building). Create low-fidelity prototype for validation ($500, 1 week). Run concierge MVP with 10 pilot customers (manual processes OK). Define clear success metrics: >35% D30 retention = PMF signal. Weekly cohort analysis to catch retention issues early.
Severity: 🟡 Medium | Likelihood: High (60%)
Description: Signup rate below projections (50 vs. 100/month). CAC higher than expected ($150 vs. $70). Paid channels don't convert well, and organic growth is slower to build. Competitive market dilutes attention.
Mitigation Strategies: Diversify acquisition channels (content, paid, partnerships, community). Build in public (Twitter, LinkedIn, blog) 3 months before launch. Create automated demo/tutorial video (reduce friction). Launch on 5+ platforms (Product Hunt, HackerNews, Reddit, etc.). Offer founding member perks (50% lifetime discount for first 100). Build referral program from Day 1 (20% commission or 1 month free).
Severity: 🔴 High | Likelihood: Medium (50%)
Description: Users cancel after 1-2 months (>8% monthly churn). Perceived value doesn't match price. Product complexity or poor UX leads to churn. Lack of ongoing engagement or habit formation.
Mitigation Strategies: Robust onboarding (email sequence, in-app tutorials, quick wins). Build habit-forming features (daily/weekly triggers). Implement churn prediction model (flag at-risk users). Proactive outreach to low-engagement users. Customer success touchpoints at Days 7, 30, 60. Offer pausing instead of canceling.
Severity: 🟡 Medium | Likelihood: Medium (40%)
Description: OpenAI/Anthropic raises prices 50-100%. Usage per user higher than estimated. Inability to pass costs to customers, jeopardizing gross margin targets.
Mitigation Strategies: Implement aggressive caching (50% cost reduction). Rate limit users (cap free tier usage). Use cheaper models for non-critical tasks. Multi-provider strategy for flexibility. Monitor cost per user daily, set alerts at $0.15/user.
Severity: 🔴 High | Likelihood: High (70%)
Description: Working 80+ hour weeks unsustainable. Quality degrades due to fatigue. Unable to maintain rapid iteration pace. Health impacts might arise, leading to project delays.
Mitigation Strategies: Schedule mandatory 1 day off per week. Use low-code tools to reduce workload. Outsource non-core work. Join founder community for accountability and support.
Metrics Tracking & Reporting Framework
**Dashboard Setup:**
- Weekly Dashboard: WAU, signup rate, churn, MRR, top bugs
- Monthly Dashboard: All 50+ metrics, cohort analysis, financial summary
- Quarterly Dashboard: Strategic review, OKRs, long-term trends
**Tools Required:**
- Analytics: Mixpanel, PostHog, or Amplitude
- Financial: Stripe Dashboard + QuickBooks/Wave
- Product: Custom admin panel + SQL queries
- Support: Intercom or Plain
- Monitoring: Sentry (errors) + UptimeRobot (uptime)
**Reporting Cadence:**
- Daily: Check North Star Metric (WAU), error rate, signups
- Weekly: Full metrics review, identify issues, adjust tactics
- Monthly: Board update (if investors), strategic decisions
- Quarterly: OKR review, roadmap adjustment, goal setting
**Metric Definitions Document:** Create a single source of truth for how each metric is calculated. Document data sources and SQL queries. Update when methodology changes.