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Growth Accounting Template for Product Growth

A growth accounting template for SaaS product teams. Covers new, retained, resurrected, and churned user tracking, quick ratio calculation, cohort...

Updated 2026-03-05
Growth Accounting
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Frequently Asked Questions

What is the difference between growth accounting and cohort analysis?+
Growth accounting shows you the composition of your active user base in each period (new, retained, resurrected, churned). Cohort analysis tracks a single group of users over time to see how their behavior changes. Growth accounting answers "what is happening to our user base right now?" Cohort analysis answers "how do users from different time periods behave over time?" You need both. The [Product Analytics Handbook](/analytics-guide) explains how to combine these methods.
How do I define "active" for my product?+
Choose the action that best correlates with the value your product delivers. For a project management tool, it might be "created or updated a task." For an analytics tool, "ran a query or viewed a dashboard." For a messaging app, "sent a message." Avoid using "logged in" because passive logins do not reflect genuine usage. Test your definition by checking whether users who meet the criteria have meaningfully different retention from those who do not.
What quick ratio should I target?+
For B2B SaaS, a quick ratio of 4.0+ is considered strong. Consumer products often need higher ratios (6.0+) because individual user churn is structurally higher. If your quick ratio is below 2.0, prioritize retention over acquisition. Adding more users to a leaky bucket is expensive and unsustainable. For context on SaaS economics, the [net revenue retention glossary entry](/glossary/net-revenue-retention-nrr) explains the revenue-side equivalent.
How often should I review growth accounting?+
Weekly for high-volume products (10K+ active users) and monthly for lower-volume products. The key is consistency. Growth accounting is most valuable when you have 6+ consecutive periods of data so you can spot trends rather than reacting to single-period noise.
How do I reduce churn if I do not know why users leave?+
Start by segmenting churned users. Look at their behavior in the 2 weeks before they churned. Common patterns: never completed onboarding, stopped using a core feature, hit a specific error repeatedly. Then interview 5-10 recently churned users. Qualitative data from even a small sample will reveal the top 2-3 reasons. You do not need a survey of 1,000 people to identify the biggest churn drivers. ---

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