Retail is one of the industries, which has got lot of touch points with customers and therefore it becomes important to understand the need and behavior of these customers.

The customer’s behavior is difficult to capture, follow and predict, with the shopping becoming more and more of a digital experience. The customer in today’s world has become more informed, smart and sensitive to various parameters like price, shopping experience and after shopping support.

But digitalization has also helped Retailers in a big way; it has changes the dynamics and has led to an outburst of data to be analyzed and to make meaningful sense out of it. The fight for the retailers today is to understand the customers and have the biggest pie in terms of market share.

This is where the Retail Analytics pitch in.

Retail Analytics helps Retailers reach out to the right set of customers. The techniques discussed below in some way or the other, label the customers into different clusters, the clusters which makes it easy for the retailers to devise strategy around them:

Market Basket Analysis: This evaluates the customer basket based on the POS data, and helps determine the product to product affinity. Retailers utilize this data to cross-sell their products, maintain inventory levels and also design customized promotional strategies. This is now readily used by e-commerce websites in devising recommendation engine for product suggestion.

Clustering Customers & Stores:  Customers are separated into different groups based on their shopping pattern and parameters like demographics, income, age and several others. Clustering can be done on customers as well as for Retail stores if the Retailer instead of treating all stores as one want to treat the stores in to different clusters and want to devise strategy around it.

RFM for Customer Loyalty: “Acquiring a new customer is ten times more costly than retaining an existing one”, that is why customer loyalty is one of the aspect which is looked upon with due importance. The RFM technique based on Recency, Frequency and Monetary value, determines the worth of a customer and helps retailer target those which are more valuable to him.

These techniques provide a “customer centric” solution which helps the retailers find out the customer set or put like customer cluster of his choice helps achieve personalization on a group basis, also in turn leads to enhanced customer experience and helps create customer Loyalty.