Investor Metrics Template for Product Analytics

At Seed, investors focus on growth rate and early retention signals. Show that you are growing fast and customers stick around. At Series A, add unit economics: CAC, LTV, and payback period. Show that growth is efficient. At Series B, add efficiency metrics: burn multiple, magic number, and Rule of 40. Show that the business model scales. The [net revenue retention definition](/glossary/net-revenue-retention-nrr) provides the precise calculation that investors expect.

Use the data you have and annualize it. If you have 6 months of data, calculate NRR over 6 months and disclose the timeframe. Investors understand that early-stage companies have limited data. What they penalize is imprecise or misleading calculations. Be transparent about the timeframe and methodology. The [retention rate definition](/metrics) covers the underlying calculation.

Yes. Investors will find them anyway during due diligence. Presenting a weak metric proactively with an explanation and improvement plan builds credibility. "Our logo churn is 6%, above the 5% benchmark for SMB SaaS. We identified onboarding as the root cause and shipped a redesigned flow in January that has improved 30-day retention by 12 pp." This is far better than hiding the number and having an investor discover it.

Add a footnote or annotation. "NRR reflects the legacy pricing model. New pricing (launched February 2026) is expected to improve NRR by 5-10 pp based on early cohort data." Investors expect growing companies to evolve their models. They penalize unexplained anomalies, not explained transitions.

At minimum, 6 months of monthly data. Ideally, 12-18 months for Series A and beyond. If your data is sparse, fill in what you have and be transparent about gaps. Start tracking these metrics today so you have a full history when you need it. The [Product Analytics Handbook](/analytics-guide) covers how to set up measurement infrastructure that feeds these metrics automatically. ---