Customer Cohort Analysis vs User Cohort Analysis: What’s The Difference?

Your product has many users. When you analyze them by cohorts, you should focus on a specific group–like revenue-driving customers–to better understand these users and create more value for them.

Best Practices
August 31, 2020
Image of Anastasia Fullerton
Anastasia Fullerton
Senior Product Marketing Manager
Customer Cohort Analysis vs User Cohort Analysis Large

When it comes to your users, you likely have a soft spot for those who drive revenue. It’s OK to admit it, you’re not parents, you can have favorites. When you run a customer cohort analysis, you’ll find that revenue-driving users are your role-model users because they’re the users that get your value prop and sustainably grow your business. They’re also your role-model users because their behaviors should be the model that shapes your roadmap so that you can create more revenue-driving customers.

Additionally, once you understand why revenue-driving users spend their money on your product or service, you can cater to their needs so they remain revenue-driving customers. This work also produces a long-lasting relationship with growing lifetime value. You can continually turn to your revenue-driving users and learn from them: What experiences create revenue-driving users? What campaigns drive upsells? What channels are likely to bring in more high-value customers?

You’ll need to understand your non-revenue-driving user base too, but the lens with which you examine it should be inherently different. You’ll need to compare non-revenue-driving users to your role-model revenue-driving users and see where their experiences and behaviors diverge. By identifying these differences and gaps, you can strategize on ways to minimize them. If you don’t take this crucial step and lump non-revenue-driving and revenue-driving users together, you will spend time and money on enhancements that don’t impact your bottom line. Customer cohort analysis helps you identify how your revenue-driving customers became revenue-driving customers, uncovers opportunities to increase their LTV, and uses them as a model to create more revenue-driving customers.

What Is Customer Cohort Analysis?

If cohort analysis shows you how different user groups engage with your product, especially around improving retention, then customer cohort analysis narrows the scope to those users who create revenue for your product, whether it’s watching an ad, buying a product, or signing up for a subscription. This analysis gives you insight into how your high-value customers engage with your platform.

Customer cohort analysis uses data to identify the people who drive revenue to help you understand who is getting value out of your product and who needs an extra nudge in order to become a high-value user. By concentrating on your revenue-driving customers, you can also use the analysis to better understand who is the best fit for your product, so you can tailor it to better meet their needs and figure out how to make more users like them.

To run a customer cohort analysis, first define the cohort by selecting those users who performed your revenue-generating event: made a purchase, watched a show, saw an ad impression or subscribed, for example. Depending on your revenue model, you may include those who subscribe at any tier, or you might focus on those who have made a repeat purchase. Once you have the cohort established, look for behaviors or attributes they have in common (you can do this in three simple clicks by applying your cohort to Amplitude’s Engagement Matrix chart). Identifying those commonalities can inform opportunities to provide more of what those customers value and nudge lower-performing users who might value those features to upgrade.

How Is Customer Cohort Analysis Different from User Cohort Analysis?

User cohort analysis evaluates the activity of your entire user base, whether or not they pay for your service. It doesn’t tell you anything about how to create more high-value customers and grow your revenue, unlike customer cohort analysis.

When companies include their entire user base in their analysis, it’s easy to make decisions that miss the nuances that keep users coming back. While a huge user base might get you on some lists for fast-growing companies, it won’t help keep the lights on. Just ask Groupon.

When Groupon first launched, the deal site attracted a large number of users who were interested in a bargain but were not loyal to Groupon. These high-churn users were less likely to make additional purchases unless those offers were heavily discounted, which ate into the revenue split Groupon shared with the merchant. Highlighting cheap prices attracted more users but not more profit, forcing Groupon to update their business model. Had they conducted a customer cohort analysis where they analyzed the behaviors and experiences of repeat purchasers, instead of focusing on their broader user base, they likely would have been able to narrow in on the needs of the more profitable repeat buyers and cut down on the churn.

French newspaper Le Monde, on the other hand, took advantage of a site overhaul to analyze their high-impact readers. Le Monde analyzed their data to see what content their revenue-driving users valued the most. They then tested the balance between the free content (available to all users) and paywall content (available to only revenue-driving customers) in order to best incentivize subscriptions. Their analysis showed them exactly where to nudge a user into a revenue-driving customer. Using the findings from profitable customers and what led them to subscribe, the newspaper was able to boost their online subscriptions by 20%. They continued to monitor these subscribers after the website relaunched to optimize the subscribers’ experience and improve renewals.

What Customer Cohort Analysis Can Do for You

When you narrow your analysis to your revenue-driving customers, you’re able to make cost-effective decisions. Running customer cohort analyses helps you focus on your most profitable customers and drive value in their lifecycle. For example, based on your cohort analysis, you may choose to improve:

  • acquisition
  • onboarding
  • activation
  • adoption of new product features
  • or the returning user experience

You can personalize these moments for your role-model users, and still find ways to improve them for non-revenue-driving users.

Here’s a few ideas to improve these experiences for your customer cohort:

Refine Your Acquisition Channels

Colombian tech startup Rappi started as a restaurant delivery service but has now expanded to become one of Latin America’s fastest-growing startups. While they bring in millions of new users each month, not all of those users make a purchase.

Rappi’s growth marketing team uses customer cohort analysis to identify high-impact segments to target with custom messaging. This personalization drove a 10% increase in the number of users who completed a first-time order. By narrowing in on these profitable segments, Rappi was also able to decrease the cost of acquisition by 30% and save money on their paid channels.

Hone Your Onboarding

By identifying the different roles your most profitable customers hold at their companies, you can tailor the onboarding process to better fit their specific questions and needs, which can improve engagement and retention.

For example, if your platform has a significant cohort of sales professionals, your product tour should concentrate on the tools that group needs for lead tracking instead of having them wade through the billing features as well. There’s no need to force them through a generic onboarding experience when you can focus on the functionality these revenue-driving customers need, get them up to speed and excited about the product faster, and then provide in-product nudges to encourage them to learn about other features that they might also find valuable.

Improve Your Product Strategically

Your list of possible product enhancements would likely take years to get through, and you probably get new suggestions from users every day. With customer cohort analysis, you can prioritize the improvements that keep your revenue-driving customers renewing.

Cornerstone, a leading talent management system, was considering optimizing a feature called “Position Search.” The product manager in charge estimated this effort would take six months and a full-time product manager to run it. But after comparing a customer cohort analysis with a user cohort analysis, they realized that this feature was barely used by their revenue-driving members. This information helped Cornerstone decide not to prioritize this optimization and save time and resources for other initiatives.

Convert More New Users to High-Value Customers

Every one of your revenue-driving customers was once a brand new user. Along their journey to becoming a high-value customer, they hit critical milestones along the way that helped propel them forward. A customer cohort analysis coupled with Amplitude’s Historical Count feature helps you identify those milestones so that you can nudge new users to achieve them, putting them on the path to becoming a high-value customer.

Adding milestones to your customer cohort analysis can tell you how many articles a reader needs to consume before subscribing to your publication, how many contacts a SaaS user needs to add to be retained, and help you identify the milestones you haven’t even thought of yet.

Focus on Profitability

There are times when a company would want to put all their efforts behind growing their user base, regardless of how many of those users actually open their wallets. But to transition to profitability, you need to focus on creating and retaining more revenue-driving customers. By using customer cohort analysis to understand how your revenue-driving clients find and use your platform, you can avoid costly and time-consuming enhancements that don’t increase your users’ LTV or create more revenue-driving customers.

About the Author
Image of Anastasia Fullerton
Anastasia Fullerton
Senior Product Marketing Manager
Anastasia is passionate about sharing powerful stories and sour candy (if you live in SF check out her favorite spot, Giddy Candy, on Noe St). Since she got her degree in engineering from Stanford, she’s been digging through data to find strong stories. At Amplitude, she helps companies understand the impact of empowering their teams with analytics and building better customer experiences.