How to analyze size and segment-based cohorts

How to analyse size and segment-based cohorts

Customer churn reduction and retention are vital concepts for any subscription-based business. There is extensive literature that proves that new customer acquisition is five to ten times costlier than the cost of retaining an existing customer.

Oftentimes, this analysis starts with basic cohort analysis and top-of-funnel engagement management metric definition. A cohort is a group of users, i.e., a customer segment, who shares a common characteristic or experience over a defined period. These characteristics might be date/month that they were acquired, the channel of acquisition, the customer segment, and the actions they are taking within the product like downloading the app, using a feature, completing a purchase, and so on. There are four key categories for cohort analysis: Size-based, segment-based, time-based, and behavioral.

Cohort analysis can be especially useful for product managers who are looking to improve their customer retention strategy.

Let’s walk through a few examples to see how…

? Customer size and segment-based cohort analysis work

? And how each approach provides new insights to help your business retain more customers

Size-based cohorts

By leveraging size-based cohorts, the product manager learns which size of customers are showing the highest and the lowest retention. Below is an example to explain this further

In the above example, we have covered the retention rate for four customer cohorts over a four-month period since they converted into a paid customer. Each cohort is created based on the size of the company in terms of the number of employees.

So, based on this example:

? The first cohort has 58 companies with 1-50 employees

? The second cohort has 74 companies with 51-500 employees

? The third has 68 companies with 501-5000 employees

? And the fourth has 46 companies with 5001-10000 employees

Let’s analyze their retention over a four-month period. If we look into the 501-5000 size cohort, we see that 92% of the original 68 customers acquired remain after four months. That's nearly 62 customers left with only 6 customers churned. This indicates that the product is the most successful with customer size in the range 501-5000.

This customer size has 16% better retention rate than the second-best cohort of 51-500 size customers. The product manager can use these insights to redirect the sales and marketing efforts to the 501-5000 customer size cohorts to further drive retention. Perhaps they alter the pricing to see if that improves retention for the smaller to mid-sized cohorts. In this example, we can see a 50% churn in the 1-50 customer size cohort. This could be an indicator that since this cohort is comprised of small and start-up businesses having smaller budget, they tested the product to get quick returns and churned when they could not achieve short-term gains. The product manager can then look into different ways to improve the product, so it quickly contributes to improving the sales of these small businesses. The other option could be offering price discounts for this customer size cohort.

Segment-based cohorts

A segment-based cohort can be a group of customers who have signed up for a particular level of service within the product, or customers who are using a sub-set of features within the product. An analysis of these segment-based cohorts provides a product manager with a deeper level understanding of the interests, needs, and wants of each segment. They can then design customized services, product service levels or features for a particular segment-based cohort to reduce churn and improve overall customer retention.

In the above example, we have covered the retention rate for three customer cohorts of a product over a four-month period since they converted into a paid customer. Each cohort is created based on the level of service – basic, intermediate, and advanced plans purchased by the customers. In this example, we see...

? The first cohort has 68 customers using the basic service level

? The second cohort has 74 customers using the intermediate service level

? And the third cohort has 58 companies using the advanced service level

As we can see, the advanced service level customers have churned at a much faster rate than the customers who purchased the basic level service package, and this could either be due to the advanced services being too expensive or that the basic level services are better and have fulfilled the needs of most customers. So, a customer service-level cohort analysis helps the product manager better determine which kind of service fits a particular segment of the customers. It’s often helpful to compare more than two types of cohort analysis to derive deeper insights. For example, when comparing the service-level and customer-size based cohorts, the data may show that the 501-5000 customer size customers are the biggest group in the basic service-level cohort. This could be a powerful “A-ha” moment for the product manager, who can then leverage this insight to optimize campaigns and improve paid customer conversion for the basic service level by focusing on the 501-5000 customer size.

Applying segment and size-based cohort analysis

Cohorts make up a key part of business analytics, allowing a company to gain new insights and spot patterns in their customers over time. Armed with these insights, product managers, marketing teams, and developers can tailor their products and campaigns and improve customer retention. Interested in improving your customer retention strategy by leveraging modern, cloud-based tools? Contact us to learn how the experts at Neal Analytics can help your business with cohort analysis and go beyond the basics with predictive cohorts, segmentation, lifetime value modeling, and more.