Case invited for 4th AIMA -ICRC Case Writing Competition | 9th , 10th & 11th May 2024    | Subscription Benefits
Case Study

Customer Analytics at Flipkart.Com

Bhansali Naveen , Rudravaram Jitendra, Grover Shailaja, Unni Krishnan Dinesh Kumar
Analytics (6519), Statistical Analysis (1210), Customer Churn (10334) , Customer Profitability (2040) , Customer Retention (2042), Customer Life Cycle (30474)


Flipkart, the poster child of Indian e-commerce, was an early entrant in the nascent Indian e-commerce market and quickly established itself as the leading company in this space. Flipkart has grown into an online retail giant, valued at over USD 15.2 billion as of 2015. Flipkart has been selling over 30 million products from more than 50,000 sellers in 70+ categories as well as has 30 exclusive brand associations with in-a-day guarantee in 50 cities and same-day guarantee in 13 cities. Flipkart was 33,000 people strong and had over 50 million registered users with over 10 million daily visits and 8 million shipments per month.

Flipkart has been putting in much effort and emphasis on the use of Analytics in every aspect of decision making. Headed by Ravi Vijayaraghavan, the analytics team had over 100 data scientists in 2015. Customer churn is a major concern for Flipkart since it has direct impact on Customer Lifetime Value (CLV). CLV is an important measure to differentiate customers, which can further help the organization to manage them effectively.

The main challenge in calculating the lifetime value of customers of e-commerce companies such as Flipkart is that the exact life of the customer is unknown owing to data truncation, that is, the actual point in time of customer churn, which may not be identified in e-commerce, since there would be no prior communication from the customer about the churn. Hence, traditional models of CLV calculation may not be appropriate for e-commerce companies such as Flipkart. 

Learning Objective 

The case may be used in Business Analytics and Big Data courses of MBA or Executive MBA programs to teach customer churn, customer lifetime value (CLV) and use of Markov chain (MC) to calculate CLV.  The learning objectives are:

  1. Learn to model customer churn using Markov chain.
  2. Learn to construct Markov chain models using recency, frequency, and monetary value (RFM) concepts.
  3. Predict probability of churn and time taken to reach the churn state.
  4. Calculate customer lifetime value using MC. 


  • Pub Date:
    20 Jan 2016
  • Source:
  • Discipline:
    Marketing Management
  • Product#:
  • Keywords:
    Analytics (6519), Statistical Analysis (1210), Customer Churn (10334) , Customer Profitability (2040) , Customer Retention (2042), Customer Life Cycle (30474)
  • Length:
    Pdf : 15 page(s) ,

Related Items