Cohort Analysis with python

  1. It helps to understand the user behaviour that might the affect the business in various other ways
  2. It can also help to analyze the customer churn rate
  3. It helps in analyzing the most important aspect i.e. hitting the point where the customer engagement can be increased.
  1. Time Cohort
  2. Behaviour Cohort
  3. Size Cohort
imported libraries
dataset imported with top 10 rows
  1. Charging period: String portrayal of the year and month of a solitary exchange/receipt.
  2. Associate Group: A string portrayal of the year and month of a client’s first buy. This mark is normal to all solicitations for a specific client.
  3. Associate Period/Cohort Index: Full portrayal of a client’s stage in their “life expectancy”. The number addresses the quantity of months since the primary buy.
heatmap showing the cohort analysis metric

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Advait Dharmadhikari

Advait Dharmadhikari

I am a student studying Business Analytics and Data Science.