
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 competitive landscape of SaaS, understanding customer behavior patterns is not just advantageous—it's essential. Cohort analysis stands out as one of the most powerful analytical tools available to SaaS executives seeking to make data-driven decisions. By tracking groups of users who share common characteristics over time, this method reveals insights that traditional metrics often miss.
Cohort analysis is an analytical technique that groups customers who share common characteristics or experiences within defined time periods, then tracks their behavior over time. Rather than looking at all users as one unit, cohort analysis segments users based on when they were acquired (time-based cohorts) or specific traits they share (segment-based cohorts).
For example, a time-based cohort might be "all customers who subscribed in January 2023," while a segment-based cohort could be "enterprise customers who activated the collaboration feature."
The power of cohort analysis lies in its ability to isolate variables and identify patterns that would otherwise be obscured in aggregate metrics. By tracking these distinct groups, you can see how different cohorts behave across their customer lifecycle.
While overall growth metrics might look promising, cohort analysis can reveal underlying issues. For instance, your total monthly recurring revenue (MRR) might be growing, but cohort analysis might show that recent customer cohorts are churning faster than earlier ones—an early warning sign of product-market fit deterioration.
According to OpenView Partners' 2022 SaaS Benchmarks report, companies that regularly perform cohort analysis are 26% more likely to identify churn risks before they impact overall metrics.
Cohort analysis allows you to measure how specific product changes, feature releases, or pricing strategies affect distinct customer segments over time. This isolates the impact of your initiatives from other variables.
For instance, if you implemented a new onboarding flow in March, you can compare the retention rates of the "March cohort" against previous cohorts to quantify the improvement.
Not all customers are created equal. Cohort analysis helps identify which customer segments have:
This insight allows for more targeted marketing, sales, and product development efforts.
Historical cohort performance provides a solid foundation for revenue forecasting. By understanding how past cohorts have behaved, you can build more accurate models for how newer cohorts will perform, leading to better financial planning.
Start by determining what cohort grouping makes sense for your business:
Next, decide which metrics to track. Common SaaS cohort metrics include:
Cohort analysis is typically visualized through cohort tables or heat maps, where:
Most analytics platforms like Amplitude, Mixpanel, or even Google Analytics offer cohort analysis functionality. For custom analysis, tools like Tableau or Python libraries can be utilized.
When analyzing cohort data, look for:
According to Profitwell research, a 5% improvement in retention can increase profit by 25-95%, making retention pattern identification particularly valuable.
Cohort analysis isn't valuable unless it drives action. Use your findings to:
Slack's meteoric rise to a multibillion-dollar valuation wasn't accidental. Their product team meticulously tracked cohort-based metrics, particularly around team messaging activity.
They discovered that teams that exchanged 2,000+ messages were significantly more likely to remain customers. This "magic number" became a north star metric, and Slack optimized their onboarding to help new customers reach this threshold faster.
By tracking this metric across cohorts, Slack could see how product changes impacted activation rates over time. According to former Slack Product Manager Kenneth Berger, this cohort-based approach was instrumental in their growth from startup to enterprise-ready platform.
Cohort analysis provides a powerful lens through which SaaS executives can understand customer behavior, product performance, and business health. By segmenting customers into meaningful groups and tracking their behavior over time, you can uncover insights that aggregate metrics simply can't reveal.
In an industry where retention often determines success, cohort analysis serves as a critical tool for identifying improvement opportunities and measuring the impact of your initiatives. The SaaS companies that excel at leveraging these insights are the ones most likely to optimize their growth, reduce churn, and maximize customer lifetime value.
For SaaS executives looking to elevate their analytics capabilities, implementing robust cohort analysis should be considered an essential component of your data strategy—not just a nice-to-have.
Join companies like Zoom, DocuSign, and Twilio using our systematic pricing approach to increase revenue by 12-40% year-over-year.