Friday, July 12, 2024

What is Customer Cohort Analysis: A Complete Beginners Guide

Customer cohort analysis is a subset of behavioral analytics that deals with the grouping of customers sharing similar interests. It is a technique that every successful company uses to monitor user engagement and provide value that is highly customized to its users.

As per a 2022 survey, 62% of the respondents expect a personalized experience from a brand to build loyalty. And that’s why you should be well aware of your customers’ demands and give them a personalized experience. To make sure of that, we have prepared a detailed guide for you so you can level up your business with customer cohort analysis. Let’s get right into it.

What is Customer Cohort Analysis?

As the name suggests, Customer cohort analysis refers to analyzing particular groups of customers who share similar behavior. For cohort analysis, companies collect data based on their customers’ behavior towards their products or services over a specific timeframe. After that, they categorize them into groups based on common characteristics. These groups are called customer cohorts. Once the grouping is done, companies analyze the data for each customer cohort.

For example, 50 people signed up for a newsletter in the first month and 30 people in the second month. However, a closer analysis of these customer cohorts helped the company identify a fascinating trend. They found that readers of the second month were more active than the ones of the first month. Now, the company will closely examine the case and determine the reasons behind this difference. So, the customer cohort analysis helps the marketing team change their strategy and try to fill in the gaps.

Why Perform a Customer Cohort Analysis?

Customer cohort analysis is used by business professionals, organizations, and stakeholders to understand the psychology of their customers. It helps them to meet customers’ expectations and improve retention rates. If you also want the same for your business and increase customer retention, cohort analysis is your key. Here are some benefits of it that you don’t want to miss out on:

1. A Better Understanding of Customers

As you keep monitoring the usage patterns of your customers, you gradually start gaining a deep understanding of their interests, preferences, and expectations. When you know your customers well, you can easily address their pain points and market your offerings in a better way.

2. Increased Customer Retention

The data extracted from customer cohort analysis is the best resource for learning your customers’ behavior patterns. With this data, you can improve their experience and incentivize them to stick around. It can include opening discount offers for special occasions, promo codes, and initiating loyalty programs that customers anticipate.

3. Tracking the Business Growth

We all know that vanity metrics are just a formality with no real value. Customer cohort analysis provides you with the real metrics of your business growth that help you determine your position and redefine your goals. It helps you identify the groups of your loyal customers who contribute the most to your company, which helps in strategic planning accordingly.

4. Personalized User Experience

Segmenting customers into specific groups helps to offer targeted and efficient solutions to their issues. Customers appreciate when the products or services are perfectly tailored to address their individual needs. Personalized user experience is one of the ways to make your customers fall in love with your services.

5. Reduced Churn

Cohort analysis helps you identify the stages when users churn in the customer lifecycle. Knowing the reasons, you can make informed decisions to change the course of events leading to churn. You will also be able to come up with a practical strategy that reduces churn and increases customer retention.

Types of Cohort to Analyze

Based on different factors, you can form several types of cohorts to analyze your customers’ actions. Let’s have a closer look at each of them:

1. Based on Time

These are the cohorts of customers who share the same time frame. The people who bought your products during a specified time are one cohort. Similarly, depending on your sales cycle, you would have different customer cohorts who signed up during different periods. 

For example, if your sales cycle is monthly, you can categorize cohorts simply by tracking the number of customers who purchased your goods or services in a particular month. Then, cohort analysis is performed, which shows user engagement with your products of cohorts from every month. Based on the difference in behavior of the cohorts, you can identify the reasons behind the churns and improve your marketing strategies.

2. Based on the Type of Purchase

It refers to the customers who have bought the same kind of product or subscribed to the same pricing plan. Customers are grouped based on the type of purchase they have made in the past. After customer cohort analysis, you can find out the different needs of different cohorts.

For example, customers who purchased a product with basic functionality might be looking for a simple solution at an affordable rate. At the same time, the ones who have bought the same product with advanced functionality must be willing to spend more on advanced features. However, due to its higher price, not many people tend to keep up with the advanced product. This way, analyzing the churn rate can help you understand what products are suitable for which group.

3. Based on the Size

Companies have customers of different sizes. There can be small startups, medium-sized businesses, and established enterprises too. Based on the size of customers, they are categorized into cohorts to meet the different needs of every customer.

A small, newly started business has a low budget and tends to possess a higher churn rate. On the other hand, well-established businesses can spend more and use your products or services for a longer time period. Your company needs to handle both cohorts differently. You can see that many brands have different programs pre-designed to offer to different sizes of customers. You can do such things for your brand as well.

Example of a Customer Cohort Analysis

To fully understand customer cohort analysis, let’s discuss a fictional example of your recently launched note-taking app. To form a time-based cohort, we can categorize the users based on the date the app was launched and their retention rate over a month. You may notice that the customers who signed up in the early days have a slightly lower churning rate than the ones who signed up later. But overall, the user retention rate decreased day by day.

Now, you need to analyze and identify the points that are making the customers churn. You can try comparing your churn rate with an average churn rate for a note-taking app. After comparison, you found out that the major drop-off of customers is coming from the ones who skipped the tutorial before using the app. And they are unaware of the most useful features. At the same time, the ones who watched the tutorial are using it properly.

After the analysis, you need to change your strategy. To make sure every user watches the tutorial, you can remove the option to skip it. This will improve the retention rate.

How to Use Customer Cohort Analysis?

To conduct customer cohort analysis, you will first need to gather the customer’s data. For example, information like when they started buying your products or services and how their experience has been. One of the ways to gather customer usage information is using AI chatbots like Shulex Service GPT. It is an alternative to Intercom and helps your marketing team gather data from customers’ interactions with the AI chatbot.

Based on those insights and other ways you deploy; you can group the customers and see what problems each cohort is facing. Below are the general steps to use customer cohort analysis:

  1. Organize the raw data into a spreadsheet using database software. 
  2. Start finding common ground for cohorts and group them accordingly. You can create cohort identifiers like joining date, location, age group, education level, and many more.
  3. After creating customer cohorts, draw a comparison between behavioral cohorts. Find out the factors that are affecting the retention rate of your customers.
  4. Now, visually present your data in the form of graphs and pivot tables to gain a better understanding and work for its solutions.

When to Use Customer Cohort Analysis?

Customer cohort analysis should be used when you want to increase the customer’s lifetime value by identifying the trends and patterns in the customer life cycle. When you want to optimize the user experience, you need insights into the behavior of your customers.

Similarly, If you see customers churning after a specific event, you need to figure out what is driving them to churn. That’s when you need to use Customer Cohort Analysis to revive your business and maximize the retention rate of your customers.

Wrapping Up – Leverage the Potential of Customer Cohort Analysis

Customer cohort analysis is an effective tactic to optimize products/services and retain customers in today’s highly competitive era. When you are aware of the mindset of your customers, you can strategize your marketing campaigns and give a personalized experience to your customers.

Furthermore, it is also important to consider deploying AI chatbots, like the Shulex VOC AI chatbot. It is a more powerful alternative to Zendesk, allowing you to respond to customer queries instantly with the power of AI-trained data and gather valuable customer insights during all interactions. To wrap up, harness the power of customer cohort analysis and deploy advanced technologies to drive user engagement and boost sales!

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