Measuring Aisle productivity using path to purchase - Hypermarkets

Abstract

Abstract

In this project, we have attempted to dissect the behaviour of shoppers in the hypermarket

environment. While it involved basic secondary research to understand the industry situation, the main focus was on primary research, while we performed on the ground research in Hypercity in Ahmedabad. The work was on the overall data received from Ahmedabad.

The primary research involved two main focus areas – observation of customers at the

hypermarkets and a few interviews with the customers. We observed how customers react to visual information and try to ascertain their buying behaviour. We have also tried to cluster the customers in different categories based on their demographic profiles and based on the similarity in their buying behaviour. Then we have tried to create a decision tree for the buying process for every type of customer based on the clustering and have tried to arrive at the probability of their buying or not buying based on the chain they belong to. Thus once it is known that a particular customer belongs to a particular cluster, when he arrives at the hypermarket, it is possible to apply certain recommendation based on the observations and also ascertain the probability of these customers buying the product.

Based on the data, MS Excel was used to determine and cluster the responses according to identified categories based on buying behaviour and decision making.

Finally, certain relevant managerial implications from the findings have been given based on the supporting data.