
Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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Join companies like Zoom, DocuSign, and Twilio using our systematic pricing approach to increase revenue by 12-40% year-over-year.
In the data-rich environment of modern SaaS businesses, making sense of user behavior patterns can be the difference between sustainable growth and stagnation. Cohort analysis stands out as one of the most powerful analytical frameworks for understanding how different groups of users engage with your product over time. For SaaS executives looking to make data-driven decisions, mastering cohort analysis is no longer optional—it's essential.
Cohort analysis is a subset of behavioral analytics that groups users into "cohorts" based on shared characteristics or experiences within specified time periods. Unlike traditional metrics that provide aggregated data, cohort analysis tracks specific groups of users as they progress through their lifecycle with your product.
A cohort typically refers to users who share a common characteristic or action taken during a particular time frame. The most common type of cohort is the acquisition cohort, which groups users based on when they first signed up or became customers.
For example, all users who subscribed to your SaaS platform in January 2023 would form one cohort, while those who subscribed in February 2023 would form another. By tracking these distinct groups over time, you can identify patterns and trends that might be obscured in aggregate data.
Aggregate metrics can be misleading. Your overall monthly recurring revenue (MRR) might be growing, but this could mask concerning retention issues with newer customer cohorts. According to a study by ProfitWell, SaaS companies that regularly perform cohort analysis are 30% more likely to identify critical retention problems before they significantly impact revenue.
Cohort analysis offers concrete evidence of product-market fit by showing whether newer cohorts are retaining better than older ones. As Lenny Rachitsky, former Airbnb product lead, notes: "Improving retention curves across cohorts is one of the strongest indicators that you're moving toward stronger product-market fit."
By tracking how cohorts behave over time, you can more accurately predict how much revenue customers will generate throughout their relationship with your business. Research from Klipfolio indicates that SaaS companies with accurate CLV predictions are able to spend 28% more efficiently on customer acquisition.
When you understand how different cohorts respond to product changes, marketing campaigns, or pricing adjustments, you can make more informed decisions about where to invest resources. According to OpenView Partners' 2022 SaaS Benchmarks Report, companies that use cohort analysis to guide their decision-making grow 15-20% faster than those that don't.
Cohort analysis can reveal whether customers who join during certain periods perform differently over time, allowing you to adjust your acquisition strategies accordingly.
Before diving into cohort analysis, establish what specific questions you're trying to answer:
While time-based acquisition cohorts are most common, consider these alternatives based on your objectives:
Common metrics to track for each cohort include:
A standard cohort analysis table displays time periods across the top (e.g., months since acquisition) and cohort groups down the side (e.g., month of acquisition). Each cell shows the relevant metric for that cohort at that point in their journey.
For example:
| Acquisition Cohort | Month 1 | Month 2 | Month 3 | Month 4 |
|--------------------|---------|---------|---------|---------|
| January 2023 | 100% | 85% | 78% | 72% |
| February 2023 | 100% | 87% | 82% | 75% |
| March 2023 | 100% | 90% | 84% | 80% |
In this retention table, we can see that each successive cohort is retaining better than the previous one—a positive indicator of improving product-market fit.
While tables provide detailed information, visualizations can make trends more apparent:
According to Amplitude's Product Analytics Benchmark Report, companies that visualize their cohort data are 23% more likely to take action based on their findings.
Cohort analysis isn't a one-time exercise. Set up dashboards to continuously monitor how newer cohorts compare to older ones, especially after significant product changes or market shifts.
For deeper insights, analyze cohorts across multiple dimensions simultaneously. For example, examine retention rates for enterprise customers acquired through direct sales in Q1 versus those acquired through partnerships.
Use historical cohort data and machine learning to predict future behaviors. Companies like Zuora and ChartMogul offer sophisticated tools that can help predict which current customers are most likely to churn based on cohort patterns.
Benchmark your cohort performance against industry standards. According to a 2022 report by KeyBanc Capital Markets, top-quartile SaaS companies maintain 90-day retention rates above 85% for their ideal customer profile cohorts.
Focus on actionable metrics rather than trying to analyze every possible cohort combination. As Tomasz Tunguz, venture capitalist at Redpoint Ventures, advises: "Pick the 2-3 most important cohorts that directly relate to your current strategic priorities."
Small cohorts may show dramatic percentage changes that aren't statistically meaningful. Ensure your cohorts are large enough to draw valid conclusions.
Major market events, seasonal patterns, or competitive moves can impact cohort performance. Always consider the broader context when interpreting changes in cohort behavior.
Cohort analysis is only valuable if it drives action. The most successful SaaS companies create closed-loop systems where cohort insights directly inform product development, customer success initiatives, and go-to-market strategies.
For example, when Slack noticed that customers who completed specific onboarding actions showed dramatically better retention in their cohort analysis, they redesigned their entire onboarding flow to emphasize these key behaviors. The result was a 15% improvement in retention for subsequent cohorts.
As you build your cohort analysis capability, remember that the goal isn't just better measurement—it's better decision-making. By understanding how different user groups experience your product over time, you can create more personalized experiences, target your resources more effectively, and ultimately build a more sustainable SaaS business.
In today's competitive SaaS landscape, your ability to extract meaningful insights from cohort analysis could be your most significant competitive advantage. Start simple, focus on actionable insights, and make cohort analysis a core component of your data-driven decision-making process.
Join companies like Zoom, DocuSign, and Twilio using our systematic pricing approach to increase revenue by 12-40% year-over-year.