Retail Consumer Sector Benefits from Data Visualization & Analytics

March 2, 2017 By 0 Comments

Introduction

The Data Visualization & Analytics revolution is changing how business gets done in all sectors, and retail consumer sector is no exception. The massive retail market is making use of advanced analytics and predictive modeling, which is changing the face of this sector and helping the consumers get what they want, when they want it.

Data Visualization in Retail Consumer Sector

One of the classic use cases of Data Visualization & Analytics tech in retail though mostly in e-commerce settings is the evolution of recommendation engines. Based on a customer’s purchase history, and the histories of others like him, the Data Visualization & Analytics tell what the customer is likely to purchase next. By training machine learning models on historical data, the savvy retailer can generate accurate recommendations before the customer leaves the Web page.

This is one of the low hanging fruit problems because it is implemented relatively easily and can have an immediate impact on revenue and profit. Retailers are finding they can improve revenue uplift by generating recommendations through Data Visualization & Analytics tools, instead of using standard recommendation engines.

The Market Today

A retail consumer today want the ‘celebrity’ treatment when they engage with companies, as they expect companies to anticipate their needs, to have the products they want on-hand, to communicate with them in real time via social media, and to adapt to their needs as they change.

This is a not an easy challenge for any retailer to face, but it would be practically impossible to do without some sort of Customer 360 initiative. And considering how many customers a retailer must interact with, and how many data sets are involved with getting there, Data Visualization & Analytics technology and real-time processing is critical to making that happen.

Market basket analysis is a standard technique used by merchandisers to figure out which groups, or baskets, or products customers are more likely to purchase together. It’s a well-understood business processes, but now it’s being automated with Data Visualization & Analytics. Also, analyzing how a customer came to make a purchase, or the path to purchase, is another way Data Visualization & Analytics tech is making a mark in retail.

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