Customer Cohorts and Customer Segmentation for an E-commerce Company

Customer Cohorts and Customer Segmentation for an E-commerce Company

The Client: A leading online grocery, food-tech company based out of Mumbai, India

Client Background: The company was one of Mumbai’s premier online convenience stores. They have revolutionized the grocery shopping experience making each step of the shopping process as delightful as possible. They grocery stocks over 14,000 products and regularly introduces new products under a wide array of categories.

Geography: Asia Pacific-India
Industry: E-Commerce

PROBLEM STATEMENT
Classification of a typical purchase basket from a customer
Deciphering Customer Cohorts mapped to the purchase basket
Identifying the best promotional pack based on the Customer Cohorts developed
Designing Customer loyalty programs based on the type of basket purchase

M76 ANALYTICS APPROACH
Organize relevant transactional details like Average order size/user, Categories, Sub
categories, product and SKU’s

Profile all possible types of Food baskets and categorize the basket types
Qualify categorized baskets using capabilities such as zone, categories, brand names,
product name, subcategories and billing amount

Through our statistical processing engine, collated inputs were processed statistically to
arrive at FIVE statistically separate categories of Basket Types (Typical Food baskets) –
Customer Cohorts

Customer Cohorts (logical customer groups) were further mined to correlate to their
demographic parameters like Gender, Age, Zip code – Region/Zone

Repeat Customer Analysis and identification of their cohorts were also carried out