Are you looking to improve your website’s retention rate? If so, then you’ll need to do a retention analysis. But what is a retention analysis and how do you go about doing one?

Don’t worry! In this blog post, we’ll walk you through everything you need to know. So let’s get started!

What is a retention analysis?

Product teams can use retention analysis to answer the question “How many of our new customers return to the product?”

Retention analysis is Sometimes referred to as survival analytics. It works alongside your new-user acquisition metrics to determine the percentage user growth that converts into a recurring, profitable customer base.

Why is retention analysis so important?

User acquisition metrics are simple and exciting when you first start. They also seem to be top of mind for investors as well as executives.

Focusing too much on new users without understanding why customers stay loyal can lead to wasted acquisition resources and obscure key indicators that will help you improve customer retention.

If the marketing department spends a lot to acquire users who are likely to leave, their customer lifetime value (LTV), might be lower than their acquisition cost. The app will fail If the company continues to spend more on acquisitions than the LTV of customers.

Product teams need to analyze retention rates to determine how they can keep more of their users.

• How long can different customer personas stay around?
• How long does it take a new user of the product to return to it?
• Are recent product changes encouraging more users to return?
• What have been the negative effects of changes on retention?
• What changes can be made to increase retention?
• What is my churn rate?

Answering these questions can help Product teams to increase retention and make their product more beneficial.

In-app user behavior

Product teams need to know what’s going on within their app. This means that they must track users individually and in groups, as they engage with activities such as downloads. They can also track every action back to its source, such as an advertisement campaign, to determine which events and sources are most closely related to retention.

You can calculate retention with any action a user takes \(like log in\), or you can decide to measure only the actions you consider valuable such as sharing or converting.

Retention strategy

Next, Product teams must define what retention means to their product. First, define a goal event specific to your app and the number of times a user must return to complete it. A retention strategy For a social media app might look like a user returning within three days of their last login.

The strategy might be longer For a banking app. For example, a bank app may expect a user to get back to their app once in a few weeks.

Example definition: A customer is considered retained if they take any action within the first twenty days. They are considered to have churned If they don’t act within 20 days.

Defined cohorts

Product teams can create cohorts of users to help them compare which cohorts have the highest retention rates. In some cases, the week that users created a new account is used to define a cohort. Each month could have four cohorts, one per week, for example.

Product teams could compare January week 1’s cohort to January week 2’s cohort or February week 1’s cohort to see if retention has improved. Alternately, cohorts could be segmented based on defining properties like attribution source, location and plan details.

Measuring retention

Product teams can calculate a variety retention rates to best reflect their business goals.

Doing retrospective retention analysis helps you answer the following question: “How many new customers remain customers?” It calculates how many members were retained over a trailing period.

As of January 1st, 28% of users who signed up for the app were retained.

That might be used to calculate user retention of a consumer music app at seven, 14 and 30 days. That might be the case for long-term contracts in marketing automation software.

Product teams can calculate retention rate by segmenting customer cohorts into their data. The results can be very informative when viewed in conjunction with each persona’s LTV. Low retention numbers may result in some personas having high potential but low LTV. teams can unlock greater value by increasing their retention.

Finally, Product teams can use acquisition sources to evaluate retention. It is not unusual for certain sources to produce customers who have very high retention rates or very low. For example, ads might bring in a lot of new users, but they quickly lose interest. Social shares might bring in users who are more loyal and who are looking for a solution.

What are the trends in retention metrics?

It is Just as important to measure retention over time. It’s more meaningful to know that a product’s 30-day retention rate is five percent compared with previous rates. Product teams will need to fill any gaps if last month’s retention rate was six percent and the previous month was eight percent. If it’s higher than four percent, that’s a reason to celebrate.

How do you analyze customer retention?

App retention is a hot topic because there is no one-size fits all solution to churn.

Every app is unique, every user is unique, and there is no one-size fits all solution. Every business must develop its own strategy, based on its customers and products.

Before you can get started with customer retention analysis you will need to answer some questions about your app.

First: What counts as an active user or inactive?

Before you can calculate retention numbers or measure churn, you must be able to identify which users have met your criteria.

Some apps consider any user who launches an app to be an active user. Some apps only consider a user active if they complete an event such as uploading a photograph, searching for information, or streaming content.

Only you can decide the best definition of your app. However, we recommend that you tie your criteria to key actions in-app that are directly related business KPIs.

Second: What are your users doing in your app?

Look beyond app launches. How meaningful is their engagement? How often do users convert? What actions or features are associated to higher retention?

Mobile marketers need real-time analytics to be successful.

Only a few seconds are left to respond to customer intent and interest. It is crucial to understand what your customers are doing in your app right now. This will allow you to create timely campaigns that hook users and increase engagement.

Once you have answered the above questions, you can measure your app’s retention rates.

So How do you calculate customer retention rates?

Calculating retention is as simple as taking the number users who are still using the site at the end of the time period, and comparing it with the number of users at the beginning of that period. Divide the difference by how many customers you had at the beginning of each period. Simply multiply 100 to calculate retention percentage.

What is a cohort analysis?

Cohort Analysis is a behavior analysis that examines a subset of users or groups of users who share certain characteristics over a time period. A “Cohort” is a subset or group that shares common characteristics. A cohort can be defined as the number of people who have downloaded the gold version of your software. You could also study their behavior separately from other users. Customers with an average basket value of over 300 dollars can be considered a cohort in e-commerce.

Understanding what cohorts are and how to conduct cohort analysis is crucial in order to measure retention rates. To calculate quarterly retention rates, I will use Cohort analysis to analyze the purchase history of an e-comm company.

Cohort Analysis is important because it focuses more upon the engagement side of things than the growth side. It is easy for a growing company to ignore or undervalue retention rates. Growth numbers often outweigh retention numbers. New customer acquisition is expensive. Constantly spending money to acquire new customers without considering retention is a bad business strategy. It can lead to high CAC and low profitability for many businesses.

Conclusion

Using retention analysis, a product team can figure out how many new users they can expect to transform into long-term, profitable customers over time.