Great products, like great relationships, require maintenance. When something feels off, you try to figure out what’s up. So, if your SaaS customer retention has taken an unexpected dip, you need to address the root causes.
Are your new features landing like a dad joke at a teenagers' party?
Is your app being ignored like that unread WhatsApp you sent to your crush?
Which acquisition channels bring in users as loyal as Grandma's Bridge Club, and which attract users with the staying power of a toddler's attention span during long car rides?
You need answers before your customer base dwindles further.
Say hello to a cohort retention analysis.
This assessment - sometimes called churn analysis - pinpoints exactly where and why users are disappearing.
What is a cohort retention analysis?
A cohort retention analysis identifies trends and patterns in SaaS customer retention, engagement, and revenue.
How it works: You divide users into cohorts based on who signs up for your product around the same time or shares behavioral characteristics. Then, you track their journey over time.
As you monitor cohorts, patterns emerge—who sticks around, who becomes super-users, and who contributes most to your bottom line. By the end, you will have a snapshot of what makes your loyal users stay and what makes the flaky ones leave.
Generally, there are two types of cohorts:
- Acquisition-based cohorts
You can group users based on when they first engaged with your product. So, if you have a mobile app, you’ll track how long users remain active after their initial interaction (daily, weekly, monthly).
Acquisition cohorts help you understand broader trends in user retention and how external factors (like marketing campaigns or product updates) impact user longevity.
Behaviour-based cohorts
You can also segment users according to specific actions they take (or don’t) within a defined timeframe, such as completing a purchase, using key features, or reaching an engagement milestone.
For example, a cohort could be users who upgrade from free to paid plans. Behavioral cohorts identify which actions most indicate user success, helping prioritize feature development and onboarding strategies.
Why does a cohort retention analysis matter?
While a cohort retention analysis is related to product usage, its insights affect your entire company in the following ways:
- Feature and Onboarding Optimization: Determine which features are user magnets and which might as well not exist. Plus, fine-tune your onboarding to turn newbies into long-term loyalists.
- Measuring Impact and Predicting Behavior: Compare how your latest crop of users stacks up against the OGs after product updates. Bonus: Get a heads-up on potential churners before they hit the “end subscription” button.
- Tailoring Strategies: Discover your product's VIP fans. Use these insights to speak your users' language in marketing campaigns.
- Refining Business Models: Decode the impact of your pricing tiers on user loyalty and lifetime value. Are your power users on the right plan, or can you upsell them to another tier?
Harness a cohort retention analysis; your product will naturally evolve into a retention and growth machine.
Cohort retention analysis vs. other analysis
What makes a cohort retention analysis unique is its ability to reveal patterns in how different groups of users behave as they continue using your product.
It’s granular and specific.
For example, “users who joined during the Black Friday promotion retain 15% better after six months, but the average order value is 10% lower than those who signed up organically in the same period.”
Returning to the relationship metaphor, just as couples drift apart if their evolving needs go unmet, customers will leave a product if it fails to adapt to changing demands or feels disconnected from the brand. Unlike the end of a relationship, which often results from an accumulation of things, cohort retention analysis can pinpoint the moment disengagement begins and track how it gradually declines.
This long-term, group-based view is something you won’t get from other types of analysis like A/B testing (which compares two specific versions of something) or funnel analysis (which looks at how users move through a specific process.)
Therefore, cohort retention analysis is good at helping you understand user retention, spot trends in customer behavior over time, and determine the long-term value of different user groups.
FYI: We're focusing on churn because revenue is crucial, but cohort retention analysis isn't just for identifying negative trends. It also shows when retention increases and why.
How to set up a cohort retention analysis
The framework for your analysis matters—seriously, with the sheer volume of data out there, you need to be specific to find actionable insights.
1. Ask the right questions
If you want to reduce churn, ask real questions, like, “Which features are the secret sauce for long-term customers versus those who ghost us?” or “How does the onboarding experience stack up against 3-month retention rates in different cohorts?”
2. Define your retention metrics
Think about the user actions that improve engagement—like finishing onboarding or using a core feature. Track these metrics, and you’ll uncover trends that matter. For example, you might find that users who click on your shiny new collaboration tool stick around longer or that your latest email campaign boosted subscription upgrades.
https://www.youtube.com/watch?v=VNxBZ7ka5J0
Y Combinator has a great video on how to choose the right metrics.
3. Define specific cohorts
If you aim to reduce churn, you might set up cohorts like those who signed up before a big feature launch, those who joined right after, and those who trickled in later. This way, you can actually see how your latest updates impact long-term retention instead of just crossing your fingers and hoping for the best.
What about tools and software?
Excel is your friend. You just plug in all the data and…jokes. Who has the time? Besides, there are tools to help you gather analytics.
*We interrupt this article for a brief marketing plug*
UXcam
Considered the world’s leading mobile analytics platform, UXcam offers cool features such as session replay, heatmaps, and funnel analysis. These allow your team to visualize how users interact with their apps in real time.
Mixpanel
Mixpanel is an event analytics platform that provides answers from your customer and revenue data in seconds. Customizable dashboards and reports make it easy to visualize and share key metrics across your teams.
Amplitude
Amplitude leverages machine learning and predictive analytics to help you understand current user behavior and forecast future trends. You can visualize sessions based on events in your product and understand the full user journey.
*Back to regular programming*
Making sense of your cohort retention analysis data
Alright, you’ve got your cohort datain front of you. Now what? If you’ve been around data geeks long enough, you know how to look for actionable insights. In the case of churn, that’s any big drop-offs in users.
Let’s say you spot a horrible 40% drop after week one. What’s going on there? Is it because your free trial’s up? Bingo - there’s something to tackle. It could be pricing that’s scaring people or clunky onboarding, for example.
Next, compare behavioral cohorts. Churn is rarely just one thing. For instance, you might learn users who finish your product tour stick around way more than those who bail. That’s gold for your onboarding strategy.
Remember, you're on a mission: find the awesome (or not-so-awesome) combos of behaviors and features that make users stay or wave goodbye. This is how you turn those graphs into real, actionable stuff.
How to use insights to improve retention
Of course, “getting it” a concept is one thing. Implementing it is another. So, let’s quickly go over common situations where cohort retention analysis reveals churn, along with potential solutions for improving customer retention.
Lapsed engagement after updates
- Challenge: 55% of users who signed up in the past month have churned since the update
- Solution: Update users about the changes, teach them how to use the new stuff, and ask them if they have any problems or questions
Pricing tier discontent
- Challenge: 43% of users in our first pricing tier show higher churn rates than others.
- Solution: Ask users what they don't like and change the product or price to make them happier. Or, offer a free trial of a better plan to show them why it's worth it.
Feature adoption lag
- Challenge: 30% of users who sign up but don’t engage with key features within the first month tend to churn quickly.
- Solution: Implement targeted in-app messages or email campaigns highlighting the benefits of key features and guides on how to use them.
Now’s a good time to discuss proactive engagement based on cohort behavior. If it's common knowledge onboarding affects cohort churn, you’d want to do something about it, right
Well, Command AI’s AI-powered assistant, Copilot, helps users get unstuck by suggesting product tours, onboarding checklists, and even performing tasks on their behalf.
Why does this matter? Acquiring new customers costs five times more than retaining existing ones. Suffice it to say our platform creates engaged users from day one - the anecdote to customer churn.
Case study: CakeResume’s cohort retention analysis
CakeResume, a platform connecting talent with enterprises through resume building, faced a critical challenge: reducing user churn. They needed to pinpoint where users disengaged and stopped converting.
Their cohort retention analysis tools:
1. Google Analytics for broad traffic insights
2. Mixpanel for detailed cohort retention analysis beyond Google's capabilities
Strategy and analysis:
They created and tracked cohorts like “Registered with no resume attached,” ‘Incomplete resume,” and “Resume completed but not published,” only to discover that their post-registration journey needed to provide users with more information on how to build effective resumes (Yes, Command AI could have helped here).
Results:
Once they’d improved post-registration email campaigns, they saw a 14% increase in conversion rates.
SaaS products need cohort retention analyses
A cohort retention analysis helps you pay Cupid: catch churn troubles before they start, plan irresistible features, and nurture long-term loyalty.
It’s as “simple” as realizing, “Hey, 50% of users bounce the moment we ask for credit card details during our free trial.”
(Not Command AI’s style, though. We're more about taking it slow, maybe sharing a latte and quality time on video call before we DTR - Define The Relationship.)
Romantic notions aside, cohort retention analysis may not provide a "happily-ever-after" for product-led SaaS businesses. Still, when executed correctly, it can lead to you "happily developing ever forward."
