
Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Join companies like Zoom, DocuSign, and Twilio using our systematic pricing approach to increase revenue by 12-40% year-over-year.
In today's data-driven SaaS landscape, understanding customer behavior is no longer optional—it's essential for sustainable growth. While traditional metrics like MRR and churn provide valuable snapshots, they often fail to reveal the deeper behavioral patterns that drive your business outcomes. Enter cohort analysis: a powerful analytical technique that groups users based on shared characteristics and tracks their behavior over time. For SaaS executives seeking to make informed strategic decisions, cohort analysis offers clarity amid the noise of aggregated data.
Cohort analysis is an analytical method that segments users into groups (cohorts) based on shared characteristics or experiences within defined time periods. Rather than looking at all users as a single unit, cohort analysis tracks how specific groups behave over time.
The most common type of cohort grouping is acquisition-based, where users are segmented by when they first signed up or became customers. However, cohorts can also be formed around:
By isolating these groups and analyzing their behavior separately, patterns emerge that would otherwise remain hidden in aggregate data.
Aggregate metrics can be misleading. For example, your overall retention rate might appear stable at 85%, but cohort analysis might reveal that retention for recent customer cohorts is actually declining to 70%, masked by the exceptional performance of earlier cohorts. This early warning system allows you to address issues before they affect your overall business performance.
When you launch new features or product improvements, cohort analysis helps determine their actual impact. By comparing the behavior of cohorts who experienced your product before and after changes, you can quantify the real value of your investments.
According to a study by Mixpanel, companies that regularly perform cohort analysis on feature adoption are 26% more likely to see improvement in their activation metrics.
Different acquisition channels produce different customer behaviors. Cohort analysis reveals which channels bring in customers with the highest lifetime value, not just the lowest CAC. As David Skok of Matrix Partners notes, "Understanding cohort quality by channel is the key to efficient growth spending."
By understanding how different cohorts monetize over time, you can build more accurate revenue forecasts. This is particularly valuable for board meetings and fundraising conversations, where precision matters.
Before diving into data, define what questions you're trying to answer:
Based on your objectives, determine the most relevant way to segment your users:
Common metrics for cohort analysis include:
A typical cohort analysis is represented in a table format:
| Cohort | Month 1 | Month 2 | Month 3 | Month 4 |
|--------|---------|---------|---------|---------|
| Jan '23 | 100% | 86% | 75% | 70% |
| Feb '23 | 100% | 82% | 74% | 68% |
| Mar '23 | 100% | 84% | 73% | – |
| Apr '23 | 100% | 80% | – | – |
Look for patterns such as:
Classic retention counts users active in a specific period, while rolling retention counts users active in that period or any later period. According to Amplitude's 2023 Product Report, rolling retention provides a more optimistic but often more accurate picture of long-term engagement.
More sophisticated organizations are using machine learning to predict future cohort behavior based on early signals. This allows for proactive intervention before churn happens.
Brian Balfour, former VP of Growth at HubSpot, notes that "the best retention strategies come from predicting which users will churn based on their behaviors in the first 7 days."
Instead of analyzing cohorts based on a single variable, advanced analysis can segment users based on multiple factors simultaneously. This reveals more nuanced insights about user behavior and preferences.
Slack famously used cohort analysis to identify that teams who exchanged 2,000+ messages were significantly more likely to remain customers. This insight led them to redesign their onboarding to encourage more team communication, resulting in a 11% improvement in activation rates.
Dropbox used cohort analysis to discover that users who used their product across multiple devices had significantly higher lifetime value. This led to a revised engagement strategy focused on cross-platform usage, increasing overall LTV by 18%.
Be cautious when comparing cohorts from different seasons without accounting for natural business cycles.
Allow cohorts sufficient time to mature before making major decisions based on their behavior.
Newer cohorts are naturally larger than older ones (due to company growth), which can skew comparisons if not properly normalized.
Focus on actionable insights rather than getting lost in endless segmentation possibilities.
Most modern analytics platforms support cohort analysis out of the box:
Cohort analysis transforms how SaaS executives understand their business by revealing patterns that aggregate metrics simply cannot. In an increasingly competitive landscape, this deeper understanding of customer behavior becomes a significant competitive advantage.
The most successful SaaS companies today don't just track what's happening; they understand why it's happening by looking at how distinct customer groups behave over time. By implementing cohort analysis as a core component of your analytics strategy, you'll make more informed decisions, allocate resources more effectively, and ultimately build products that better serve your customers' evolving needs.
Whether you're troubleshooting retention issues, optimizing acquisition channels, or planning your product roadmap, cohort analysis provides the clarity needed to move forward with confidence.
Join companies like Zoom, DocuSign, and Twilio using our systematic pricing approach to increase revenue by 12-40% year-over-year.