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Cohort Analysis

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Want to retain your customers then you are at the right place. It can be achieved by Cohort Analysis but the question is how this analysis helps in achieving it. Let's get started by understanding it. Cohort Analysis is used by the analyst to determine the user engagement of customers over time. To be more precise it helps to know whether our user engagement is increasing or decreasing over a period of time. It is done to know the level of user engagement and the customer churning rate in any organization. 

In marketing, the cohort is referred to as the group which possesses similar characteristics or traits, and this analysis helps us to divide customers based on their behavior. To get a better understanding of your audience you need to perform such analysis on regular basis. It can be performed in almost every analytical tool mostly organizations prefer Google Analytics but I have done it in Tableau. 



This analysis is done in Tableau. Let me walk through it and explain what it implies. Let's focus on the grand total column on the side it represents the number of customers acquired in a particular month. It is evident that by the end of last month the percentage of a customer acquired is quite lower as compared to the first month. When we talk about the grand total at the bottom it signifies the percentage of customers who repeat purchases in a particular month. It can be seen that at end of last only 1.33% of total customers repeat the purchase.

The above-mentioned analysis is performed with Google Analytics with a different dataset but it represents a similar story. The customer retention rate is changing from week to week. When you obtain a higher retention rate it is shown by a darker color.

Such analysis is quite common in marketing as it will help any organization to know their customers in a much better way also they will know when to launch any marketing campaign. It is one of the most powerful analyses because it will help you in making the strategies that are suited to the target audience. It is a pivotal analysis in data-driven decision-making. It will help to raise target questions and make much more informed decisions which can help to increase the revenue.

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