How Cohort Analysis Improves Retention & Reduces Churn

How Cohort Analysis Helps Product Teams

Cohort analysis is a great way to identify how well your product is meeting the needs of different groups of users. It’s a crucial step in knowing where to do further analysis and make changes that will keep customers around for longer—once you identify a group of users with low retention rates, you can dig into those groups’ traits and behaviors to find correlations and explore the underlying reasons for their churn.

Here’s how it’s used:

Early in the customer lifecycle: Cohort analysis helps teams increase adoption by analyzing the ways that groups of users act in the first few days, weeks, or months of using your product or site. By showing which groups of users respond best (and worst!) to different features, marketing initiatives, and support efforts, cohort analyses can uncover patterns that guide you when figuring out when to provide support, send emails, or offer in-product tooltips. Later, it can be used to measure the effectiveness of these approaches. Product teams can also use this data to understand how much each feature has contributed to adoption and make adjustments to their roadmap.

As people use the product over weeks or months: Cohort analysis will reveal how long different groups of users stay engaged and when they’re likely to churn. Product teams can see how often each group performed a particular action, like logging in for a session or interacting with a feature, before their usage dropped off. They can then dig deeper into the traits of the worst-performing cohorts to find the underlying cause of churn.

How to Get Started with Cohort Analysis

The main goal when doing cohort analysis is to group users in a way that surfaces actionable discrepancies between them.

For example: you can start by comparing retention data among different groups of users, segmenting users based on simple demographics (like region or industry) or referral channel to see which groups have the worst retention metrics.

In the example above, users that were acquired through paid search drop off more and churn faster than other channels. You can use this insight to dig deeper into the paid search, further segmenting the cohort by key actions users take in the product.

How to Act on Your Cohort Analysis

Once you analyze and interpret your data, you’re ready to start testing hypotheses on why the groups with lowest retention rates churn faster than others. For example:

• You can modify your marketing to target groups with lower churn rates.

• You can see what actions your high-performing groups take in your product, and nudge more users towards those behaviors.

• You can see where in their lifecycle customers best respond to new feature emails, and start calibrating your outreach accordingly.

After rolling out these tests, use analytics tools like Heap to see how successful they are.

Cohort Analysis for SaaS Companies

Cohort analysis is a great way to understand potential reasons for churn, and to identify the features, offers, and pricing tiers that drive longer-term retention for software providers.For SaaS companies, improving customer retention can be the difference between growth and stagnation. When user engagement starts to trend downward, quickly running a cohort analysis can help avoid churn. The product team can pinpoint common characteristics and behaviors, like their industry or the type of data they upload, among less-active user groups. They can then re-engage them with new marketing campaigns, remarketing programs, or feature improvements based on specific customer behavior.As a SaaS company, you can use cohort analysis to:

• Orient your product roadmap to meet the needs of your most devoted paying customers.

• Direct your marketing to acquire the customers most likely to make repeat purchases or spend more.

• Use insights from different moments in the customer journey to optimize adoption, onboarding, feature discoverability, and ongoing customer support.

The impact of increasing retention even a few percentage points can be huge for product teams:

To see more strategies for improving retention across the customer journey, download The Heap Guide to Retention.

Cohort Analysis for eCommerce Companies

eCommerce companies can use cohort analysis to analyze consumer behavior and find out which products, demographics, and seasonal patterns most correlate with repeat purchases and large lifetime value.Conversion is usually to top use case of cohort analysis for eCommerce brands. User groups who take certain behaviors early, like browsing specific pages, favoriting products, or reading reviews, might be more likely to purchase specific items or add more items to their cart. But to figure out what those exact behaviors for your ecommerce website or app, you must run cohort analysis and do further analysis an interesting pattern appears.As an eCommerce company, you can use cohort analysis to:

• Focus your marketing dollars on customer segments most likely to make repeat purchases.

• Build a smooth, high-conversion funnel that takes new users from the awareness level all the way to a repeat, loyal customer status.

Eliminate friction by identifying user behaviors that tend to lead to dropoff.

If you’re look to optimize your eCommerce funnel, read our complete guide.

The Best Analytics Tools for Performing Cohort Analysis

There are several ways to get started using cohort analysis, but the most comprehensive approach is via a product analytics platform like Heap. This option provides you complete knowledge about how people interact with your product, and offers the greatest number of insights around which behaviors correlate with long-term value and high retention.

Using Product Analytics for Cohort Analysis

Product analytics platforms offer the greatest flexibility and the greatest depth in analyzing cohorts. While Google Analytics provides just acquisition data, product analytics gives you information about cohort behavior throughout the customer journey.

For example, Heap automatically captures all event data in a product or site (clicks, swipes, views, form-fills, and more) and allows anyone to examine that data through intuitive dashboards and reports. Product teams can easily see how customers most (and least!) likely to churn behave—what features they use the most, how often they log in, and what their common workflows look like.

Locating the cohort groupings that surface the most information can be tricky. As the owner of a digital product, you never know which behaviors or activities will most correlate with retention or churn. (We’re often surprised by what we find!) For this reason it’s crucial to invest in a solution that tracks every event on your site. In most tools, you have to decide in advance which events matter. This seriously limits the amount of information you can gather, especially when it’s information that may reveal something unexpected.

The Google Analytics Cohort Report: A Good Start, but Not Enough

Google Analytics has a cohort report that allows you to compare various user groups. However, this tool has significant limitations.Google Analytics is best for understanding how groups of users behave based on their acquisition date. It can be tedious to set up, but once you have the right events tracking in GA you can compare different cohorts to see which actions are likely to drive greater retention.

If you’re looking for Google Analytics alternatives, take a look at this list of options.

Because Google Analytics doesn’t track unique user identities without time-consuming manual setup, there are some serious limitations that keep product teams from digging as deep as they’d like into user behavior. The tool also doesn’t integrate with other customer touch points, like support tickets or email activity, so you might not be able to go as in-depth as you need to in order to get actionable answers.Since Google Analytics only offers cohort reports based on predefined events and pageviews, you’ll be limited to what you decided to track initially—if you need to compare cohorts based on new events, you’ll have to manually add them then wait months for the newly populated data.

Get Started with Heap for Free

Heap’s product analytics platform helps teams analyze behavioral cohorts and break down acquisition data based on every activity. Autocapture gathers all event data automatically, eliminating the need for manual event tracking and giving product teams access to all the behavioral data they need to optimize their product strategy for greater retention.