Cohort Analysis on Online Retail Data 2011
Cohort analysis is a subset of behavioral analytics that takes the data from a given eCommerce platform, web application, or online game and rather than looking at all users as one unit, it breaks them into related groups for analysis. These related groups, or cohorts, usually share common characteristics or experiences within a defined time-span.
Cohort analysis is a tool to measure user engagement over time. It helps to know whether user engagement is actually getting better over time or is only appearing to improve because of growth.
Cohort analysis proves to be valuable because it helps to separate growth metrics from engagement metrics as growth can easily mask engagement problems. In reality, the lack of activity of the old users is being hidden by the impressive growth numbers of new users, which results in concealing the lack of engagement from a small number of people.
I did data pre-processing first before deep analysis like data visualization etc. The analysis keeps focus on customer and revenue. It aims to improve user or customer retention in our company and find out the customer behavior for the certain time of period. Further, the description of data (variables) is listed on table:
These are few examples of data visualization on the cohort analysis. You can read the detail of analysis in my report (PDF) file by go over my github repo.
For more detail, feel free to go over my Github repository!