.png)
Estd 4.22.2023
In the competitive SaaS landscape, understanding customer behavior isn't just beneficial—it's essential for sustainable growth. While many analytics tools provide snapshots of user activity, they often lack the longitudinal perspective necessary for strategic decision-making. This is where cohort analysis comes into play, offering executives a powerful lens through which to view customer lifecycle patterns and make data-driven decisions.
What is Cohort Analysis?
Cohort analysis is a subset of behavioral analytics that groups customers into "cohorts" based on shared characteristics and tracks their behaviors over time. Unlike traditional metrics that provide aggregate data, cohort analysis examines how specific customer segments interact with your product throughout their lifecycle.
A cohort represents a group of users who share a common characteristic or experience within a defined time period. The most common type is an acquisition cohort—users grouped by when they first became customers. For example, all customers who signed up in January 2023 would form one cohort, while February 2023 sign-ups would form another.
David Skok, venture capitalist and founder of For Entrepreneurs, explains, "Cohort analysis is the most meaningful way to understand if your business fundamentals are improving over time." This analysis method reveals patterns that might otherwise remain hidden in aggregate data.
Why is Cohort Analysis Important for SaaS Companies?
1. Provides Accurate Customer Retention Insights
Retention is the lifeblood of subscription-based businesses. Cohort analysis provides a precise view of retention patterns across different customer segments and time periods.
According to research from ProfitWell, a 5% increase in customer retention can increase profits by 25% to 95%. Cohort analysis helps identify exactly where and why customers churn, allowing for targeted retention strategies.
2. Reveals True Business Health
Aggregate metrics can mask underlying problems. For instance, overall revenue growth might look positive while retention rates are actually declining—a serious red flag for SaaS businesses.
Jason Lemkin, founder of SaaStr, notes that "cohort analysis is the only way to truly understand if your SaaS business is getting healthier over time or just appearing to grow through increasingly expensive customer acquisition."
3. Evaluates Product Changes and Feature Adoption
When you launch new features or make significant product changes, cohort analysis helps determine their impact on specific user segments. By comparing cohorts before and after changes, you can measure the actual effect on customer behavior and engagement.
4. Optimizes Marketing ROI
Understanding which acquisition channels produce customers with the highest lifetime value allows for smarter allocation of marketing resources. According to a McKinsey study, companies that use customer analytics extensively are 23 times more likely to outperform competitors on customer acquisition.
How to Measure Cohort Analysis
Step 1: Define Clear Objectives
Before diving into cohort analysis, establish what you want to learn. Common objectives include:
- Understanding retention patterns
- Evaluating the impact of product changes
- Comparing acquisition channels
- Identifying factors influencing customer lifetime value
Step 2: Choose Your Cohort Type
While time-based acquisition cohorts are most common, consider other segmentation options:
- Acquisition cohorts: Grouped by when they became customers
- Behavioral cohorts: Grouped by actions taken (e.g., users who used a specific feature)
- Size cohorts: Grouped by company size or user count (especially relevant for B2B SaaS)
- Plan/pricing cohorts: Grouped by subscription tier
Step 3: Select Key Metrics to Track
The metrics you track should align with your business model and analysis objectives:
- Retention rate: The percentage of users who remain active after a specified period
- Churn rate: The percentage of customers who cancel or don't renew their subscription
- Revenue retention: Measures how revenue from a cohort changes over time
- Gross revenue retention (GRR): Only considers downgrads and churn
- Net revenue retention (NRR): Includes expansions and upsells
- Lifetime value (LTV): The total revenue expected from a customer during their relationship with your company
- Customer acquisition cost (CAC): The cost to acquire a new customer
- LTV:CAC ratio: Measures the relationship between lifetime value and acquisition cost
Step 4: Create a Cohort Analysis Table
A typical cohort analysis table shows time periods along both axes:
- Vertical axis: When customers were acquired
- Horizontal axis: Subsequent time periods (months, quarters, etc.)
Each cell contains the relevant metric (e.g., retention rate) for that cohort at that point in their lifecycle.
For example:
| Acquisition Cohort | Month 1 | Month 2 | Month 3 | Month 4 |
|--------------------|---------|---------|---------|---------|
| January 2023 | 100% | 82% | 76% | 72% |
| February 2023 | 100% | 84% | 79% | 75% |
| March 2023 | 100% | 87% | 83% | 80% |
This table shows retention rates improving for newer cohorts, suggesting product or customer experience improvements.
Step 5: Visualize the Data
Convert your cohort tables into visualizations to make patterns more apparent. Common visualization types include:
- Retention curves: Line charts showing retention over time for different cohorts
- Heat maps: Color-coded tables where better performance is highlighted
- Stacked bar charts: Useful for showing revenue contribution from different cohorts
Step 6: Analyze Patterns and Take Action
Look for patterns such as:
- Cohort improvements over time: Are newer cohorts performing better than older ones?
- Critical drop-off points: Is there a specific time when most users churn?
- Variations between segments: Do certain customer segments retain better than others?
According to Tomasz Tunguz, partner at Redpoint Ventures, "The key is not just to measure cohorts but to build a feedback loop where insights drive product and go-to-market decisions, whose effects are then measured in subsequent cohorts."
Implementation Best Practices
Use the Right Tools
Several analytics platforms offer cohort analysis capabilities:
- Product analytics tools: Mixpanel, Amplitude, Heap
- All-in-one solutions: HubSpot, Salesforce
- Specialized SaaS metrics tools: ChartMogul, ProfitWell, Baremetrics
- Customizable visualization tools: Tableau, Looker, Power BI
Start Simple and Iterate
Begin with basic acquisition cohorts and retention metrics, then gradually add complexity as you develop a better understanding of your data.
Establish Regular Review Cadences
Make cohort analysis a regular part of executive business reviews. According to Bessemer Venture Partners' State of the Cloud Report, top-performing SaaS companies review cohort metrics at least monthly.
Combine with Qualitative Data
Complement your cohort analysis with customer interviews and feedback to understand the "why" behind the patterns you observe.
Conclusion
Cohort analysis transforms how SaaS executives understand their business by providing a dynamic, longitudinal view of customer behavior. Unlike static metrics that may mask underlying issues, cohort analysis reveals true business health and highlights opportunities for improvement.
By implementing robust cohort analysis practices, SaaS companies can optimize customer retention, improve product development, allocate marketing resources more effectively, and ultimately drive sustainable growth.
In the words of Brian Balfour, former VP of Growth at HubSpot, "The companies that win are the ones that understand their cohorts better than anyone else and use those insights to build compounding advantages over time."
As you implement cohort analysis in your organization, remember that its true value comes not from the analysis itself, but from the actions you take based on the insights you gain. Start with clear objectives, select meaningful metrics, and create a systematic approach to translating cohort insights into strategic decisions that drive your business forward.