Supermarket Case Study

INTRODUCTION

One of the new, up-and-coming supermarket chains in India wanted advanced analytics about customer movement in their store and wanted to see if they can use this data to realise actual benefits inside their stores. There was a collaborative experiment done in one of their largest stores in Delhi (25,000 square ft). The experiment was to quantify the space usage.

HEATMAPS

Agrex.ai Heatmaps tracks people across cameras inside a single retail
store to understand deeply about the behaviour of customers inside the
store. This includes information like :
1) Hot and Cold Spots
2) Movement Patterns
3) Product Engagement

ANALYSIS

Using the heatmaps generated from the cameras the analysis was done by the operational team to study the usage of different areas in the store by looking at hot and cold spots. In addition to the engagement with different
products/areas/aisles/shelves was determined qualitatively to see how “interesting” new products were for customers. Another analysis was done on the shopper flow to see exactly how customers explore the store.

RESULTS

According to the information obtained from the heatmaps, the following changes were done inside the store :
1) Some more products/advertisement were added in the areas which were determined as cold zones leading to moreproduct variety inside the store.
2) According to the product engagement, there was A/B testing done to identify if the traffic was because of the product itself or because of the location. High visibility locations were identified to stock high margin/preferable products at those locations
3) Shopper Flow was measured to identify popular paths taken and some A/B testing was done to achieve a good ratio of visibility of products

All these optimisations were done over a course of a few months and simultaneous improvements were done in floor utilisation and sales increases.