Gainsight Glossary

Retention Analysis

What is retention analysis? 

Retention analysis is the quantification of usage data that can be used to determine the potential for customer churn or retention and why they’re churning.

We all know the dangers or churn and the fruits of product-led growth, but what about the fact that one estimate ties 80% of your future company revenue to 20% of your existing customers. Combine this with the fact that it can cost anywhere between five times more to sign up a new customer than to keep an existing one, and it’s clear that there really is a dollar value for customer loyalty.

But does your B2B SaaS company know what it has to do to keep your customers not only happy but also coming back for more time and again? That is where retention analysis comes in.

To further enhance the benefits of retention analysis and simplify the communication of their impact on your bottom line, companies often create groups, or cohorts, made up of customers that share similar characteristics. This cohort retention analysis can then be used to understand trends and usage behavior over time and identify opportunities to better serve their needs.

Why is retention analysis important?

Retention analysis is different from just calculating churn. Retention analysis helps to pinpoint exactly why some customers choose to stay while others leave. Armed with this information, your company can refine its products, services and customer success strategies and plan for sustainable business growth. For example, here are some questions that retention analysis can help to answer:

  • Where in the customer journey map are customers leaving? Identifying the points to where customers stop considering your product or are leaving their subscription behind can help find which specific stages of their journey are most important to winning over your customers. This can lead to changes in sales or marketing strategies or changes in the user experience, for example.
  • Why are customers churning and what led them to that decision? Combining results from in-app surveys, NPS scores and other feedback mechanisms with customer analysis can help to identify weak spots in your product or business model and document the top causes of churn so they can be proactively addressed.
  • What can be done to improve retention? While a knee-jerk reaction may be to modify price or make modifications to the interface, your churn could be caused by something else. Are you attracting the right customers from the start? Are your peers delivering something you aren’t?

What are some key retention metrics?

Once you have grasped the value of calculating retention and diving into the results, the first place to start is to define some key retention rate metrics. Many of these metrics come right out of the box with industry-leading customer success platforms and can leverage built-in APIs to consolidate data from across your enterprise to generate custom reports and visualizations.

Some of the most common retention metrics include:

  • Customer churn rate: The number of subscribers that leave after the end of their subscription period
  • Customer lifetime value: The total dollar value or revenue a customer has and is expected to generate on your product or service
  • User engagement score: A quantitative measure that scores customer engagement with inputs such as time spent, features used and users activated
  • Net Promoter Score: A numerical summary of how likely your customers — or a segment of your customers — are to be an advocate for your product to their peers and colleagues
  • Monthly Recurring Revenue (MRR) Churn Rate: The amount of potential lost revenue resulting from churning customers

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