What are the Benefits of Cohort Analysis?
A cohort analysis refers to the study of a group of people over a specific period of time. It is one of the powerful ways used in retaining customers and is helpful for business professionals who have websites. As many visitors visit the website and convert it into more business, it is necessary to retain such visitors and monitor their activities within a particular time period.
In short, cohort analysis describes the time that is spent accessing the landing page or product. It indicates frequency and is necessary to calculate this level.
How to Use Cohort Analysis?
You need the best marketing platform to use a cohort analysis. The objective of this analysis is to break down your data into many campaigns – each one should have a specific objective so that sum of all these leads to customer retention.
You can try the following strategies after breaking your data:
1. Improve User Journey: Most of the time, your website users could when their journey becomes difficult. It can identify the exact point in the user journey when they skipping out.
2. Targeted offers: It identifies what kind of users buy the most and what kind of product they buy. Such information can be used to create coupons, offers, and free shipping to retain your existing customers.
3. Introduce rewards: Introduce rewards, points, and gamification systems for retaining your customers. With cohort analysis, it is possible to narrow down the similar audiences who can be retained after introducing rewards.
Benefits of Customer Cohort Analysis
Accuracy: This analysis is beneficial to divide the audiences into cohorts. Thus, audiences who visited the site during a specific time period are combined together e.g. the April cohort, the May cohort, and so on.
Like this, the analysis of their behavior and how they interacted over time is unaffected by the audiences in remaining groups, thus keeping the groups totally different than one another, and facilitating an accurate study.
Clear comparison of data between cohorts:
This analysis helps you compare the outcomes between two, three, or more groups. For example, if the May cohort is more engaged in the product than the April cohort, an analysis is needed on any changes that may have taken place between these two months.
