If you’re like most business owners, you know that customer retention is key to success. But what’s the best way to ensure that your customers stick around? Cohort analysis may be the answer. Cohort analysis is a powerful tool that can help you maximize customer retention and keep your business growing strong. By tracking and analyzing customer behavior over time, you can identify patterns and trends that will allow you to make better decisions about how to engage with your target audience. How to calculate cohort retention?

Before you can start using cohort analysis to improve retention, you need to understand how it works. This guide will show you everything you need to know about how to calculate cohort retention for your business. With this valuable information in hand, you’ll be able to take full advantage of this powerful tool and keep your customers coming back for more

How to Calculate Cohort Retention

There are a few different ways to calculate cohort retention, but the most common is to simply take the number of people in a cohort who are still active at a later date and divide it by the total number of people in that cohort.

For example, if you have a cohort of 100 people and 80 of them are still active after 30 days, your cohort retention would be 80%.

What is a Cohort Analysis?

To keep your existing customers, you must find out what makes them stay. Fortunately, there are tons of analytics tools available to help you with that.

Businesses have taken advantage of advances in computing, analytics, and psychology to develop new ways of retaining their customers. One method they use is cohort analysis.

A cohort is a group of people who share a particular trait over a certain period. Cohort analysis is the study of the common traits of these people.

Cohort analysis is an advanced marketing technique. It’s often difficult to grasp, even for experienced marketers.

There’s a ton of confusing terminology, such as cohorts, RFM segmentation, shifting curves, and much more.

Here’s an example.

Let’s say that you have 100 people signing up to use your app in September. Using cohort analysis, you can track how many of them continue to use the app in the days and weeks that follow.

When looking at your data, you can break down your customer base by demographic factors like age, gender, and geographic location. This can help you determine which segments of your customer base are most engaged and how they use the app itself.

Now, any analysis of a data set needs a clear goal and specific parameters to yield useful results. In cohort analysis, there are two types of analyses.

The ultimate goal of any marketing campaign is to build a relationship with the customer that extends beyond just one transaction. Customer retention is a high priority for any business.

Why should companies measure their marketing efforts by retention?

There are many benefits to focusing on customer retention.

Businesses that fail to retain customers eventually fall into a spiral of diminishing returns. That’s because acquiring a new customer is five times more expensive than keeping an existing one.

As competition increases, it’s becoming increasingly important for companies to keep customers happy. One way to do this is to use data analytics techniques such as cohort analyses, which show what actions a customer takes over time.

Types of Cohort Analysis

There are two different types of cohorts: acquisition and behavioral.

In an acquisition cohort, customers are segmented according to when they signed up for your app. This can be tracked daily, weekly, or monthly. For instance, consumer mobile apps for productivity may track their acquisition cohorts daily while business apps might track their acquisitions monthly.

In behavioral cohort analysis, users are grouped based on specific actions that they carry out in the app during a specific period. For instance, people who shared a photo on Google Photos on the same day.

Again, the period varies from app to app. For a photo-sharing app, you can track cohorts daily. For an online investment app, three months might be more appropriate.

Why Use Cohort Analysis?

Using cohort analyses, you can analyze your data in a better way. Its applications are not limited to a specific field or sector.

Cohort analysis can be used to analyze how successful a new feature is or to identify which products are growing the fastest. It can also be used to analyze which pages on a website are performing the best, or which pages are causing the most customer attrition.

In product management, this metric can be used to evaluate the adoption of new features and to help reduce customer attrition.

The following industries use cohort analysis for marketing:

• eCommerce
• Mobile apps
• Cloud software
• Digital marketing
• Online gaming
• Website security

In all these different business types, managers analyze cohorts to identify why their customers are leaving and what they can do to prevent this from happening. This brings us to the calculation of the Customer Retention Rate (CRR).

The formula for calculating customer retention rate is CRR = ((E-N)/S) X 100

Let’s break down these three components.

• E – The number of customers at the end of a period
• N – The number of customers acquired during that period
• S – The number of customers at the start of a period

To measure customer retention, subtract the new customers you gained over a given period from the total number of customers who were still with you at the end of that period. This gives a true picture of retained customers.

To calculate the customer retention rate, divide the result by the number of customers at the beginning.

A high CRR means that your customers are loyal to your brand. By comparing your retention rate to the average of other businesses in your industry, you can see where you stand in terms of customer retention.

If CRR is low, you can correct this with help from data analytics – this is where a Cohort Analysis comes in.

Measure Customer Retention With Cohort Analysis

Cohort analysis is a data-driven decision-making process.

As a marketer, you’d be in charge of running campaigns, improving customer experience, introducing new features, and so on. Cohort analysis can determine what efforts are most successful.

Cohort analysis has many benefits for marketers.

• Predicting future user behavior
• Identifying features and activities that retain customers
• Planning for customer engagement activities based on feature adoption
• Implementing a non-intrusive, data-driven marketing system

All these individual and combined efforts help maximize customer loyalty.

Cohort Analysis Using Google Analytics

Google Analytics is an incredibly powerful tool for marketing professionals who want to mine data on website traffic, key metrics, and conversions. The cohort analysis feature is especially useful, and even those who are not power users of GA can benefit from it.

To start a cohort analysis using Google Analytics, head to AUDIENCE > Cohort analysis.

At the top of this report, you’ll find several different options. These options include the metrics, the dates, and the size of the cohorts. Using these options, you can generate a report on the data.

Here are some quick definitions of each term:

• Cohort Type: The group of customers you want to analyze
• Cohort Size: The period you want to analyze (day, week, month)
• Date Range: The period you want to analyze in date range (last 2 months, last 3 months, etc)
• Metric: The cohort analysis report on specific per-user metrics.
• Goal completions
• Page views
• Revenue
• Session duration
• Transactions

How Cohort Analysis Can Help Maximize Customer Retention

While analyzing cohorts of customers can be insightful, it can be difficult to connect all the dots and draw the right conclusion.

The key to increasing customer loyalty is to break down your strategy into several different parts, each with a specific goal.

Here are some ways you can analyze your cohort data.

Tweak customer journey: When a user’s journey is too difficult, they may drop out. By analyzing cohorts, you can see when and why this happens. You can then streamline the user journey to prevent them from leaving.

Send reactivation emails: Send out an email to remind customers of your product and nudge them towards their next order. By looking at metrics such as time between orders, you can plan your reactivating email campaign accordingly.

Send targeted offers: With cohort analysis, you can identify what products your customers purchase the most. Such information can be used to make special offers, discounts, and free shipping on products that the customers are most likely to repurchase.

Introduce loyalty programs: Loyalty programs, such as reward points and similar systems, are a popular way to retain customers and increase sales. However, it’s difficult to identify which customers are loyal to your brand and which of them will stick around for a certain amount of time. With cohort analysis, you can identify which group of loyal customers are the most profitable and which of them are likely to remain that way.

Conclusion

Now that you know how to calculate cohort retention, you’ll be able to take full advantage of this powerful tool and keep your customers coming back for more.