How Big Data is revolutionizing the retail industry? [Case Studies Included]

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The retail industry has started to make the most out of big data in recent years as well.

Big data is how retailers are identifying and connecting with their target demographic today. Through the help of this technology, retailers can easily predict the demands of their customers as part of giving them a more targeted and personalized service.

Big data has enhanced the efficiency of retailers in the last few years while also increasing competition.

In hopes to get ahead in the competition, retailers are making use of big data analytics to understand what the customer wants and how they can fulfill these needs.

Big Data in Retail Industry

Following are some of the ways in which big data is revolutionizing retail industry:

1. Providing targeted service to each customer

The only measure of success for a business is its customers. If the customer is satisfied, the business will flourish. If the customer is unhappy, the business will reduce to dust in no time.

Big data has emerged as a saving grace as it holds the power to help retailers retain customers by arming them with ways to improve customer experience.

Through big data analytics, a retailer can provide targeted service to its customers. It helps study the customer’s demand and patterns so a personalized marketing campaign can be launched. This data is mined by analyzing websites, mobile applications, social media platforms, sensors, etc.

Big Data Retail Case Study – The Chatbot Revolution

This case study was conducted in the Mall of America, Bloomington, Minnesota. With over 500+ retailers, 50+ restaurants, 14 movie theatres, 2 hotels, an indoor theme park, and a museum, the mall has a vast customer base. Because of such huge numbers, it is impossible to personalize the shopping experience for each customer.

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This is where big data comes into play.

A chatbot called ELF was designed by IBM which dispensed a simple text-based service to help customers navigate the mall.

Through the data assembled by the help of this bot, the mall retailers were able to provide better personalized service to their customers.

2. Helping foresee customer demands

Predicting the next big thing gives retailers an edge in the industry.

Big data analytics helps retailers gain insights into their customers’ shopping patterns. This helps them analyze the products which are not able to carry their weight so they can be cut off and the focus can be shifted to products that are in high demand.

Understanding trends also helps in predicting what new wave is going to hit the market so preparations can be made to take full advantage of it.

This case study of how weather forecast helped predict demands for the retail industry will help in understanding how prominently big data is being used today to revolutionize the retail industry.

Big Data Retail Case Study – Weather Forecasting

A weather channel collaborated with Pantene and Walgreens to supply them with information on the impact of weather on the moods and emotions of people.

The channel also notified Pantene and Walgreens when the level of humidity will be highest thus helping them time their advertisements for hair-care products.

Anticipating humidity-related hair problems, people readily bought more hair-care products which increased Pantene sales by 10% at Walgreens for July and August. Moreover, Walgreens saw a countrywide overall increase in sales of 4% for their hair-care products.

3. Increasing efficiency by facilitating inter-departmental coordination

The inventory department and the production unit needs to be on the same page for the retail industry to run smoothly.

Big data has helped in coordinating every link in the chain in real-time. This helps the retailer identify the products in demand so that they can be stocked up to meet the market requirements.

This has optimized operations and provided better means to deal with faster product life cycles. Big data has significantly cut down costs by helping retailers understand the supply chain and enabling better product distribution.

4. Analyzing customer journey

The zig-zag journey that a customer follows before buying a product starts at ‘Awareness’, leading to ‘Research’, ‘Discovery’, ‘Purchase’, ‘Service’, and finally ends at ‘Checkout’.

Big Data helps to handle this plethora of data and analyze it.

Today customers can look up any product they want within seconds and compare prices on different platforms. Big data helps retailers steer the customer towards their products.

Another case study in big data analyzes the customer journey. The need for customers to interact directly with the retailer has been eliminated with big data analytics.

Even a single post to your social media will land you a thousand target advertisements.

For instance, I posted about having any plans for my birthday and I was presented with unlimited things I could do in different locations for different budgets.

Summary

The importance of data has been reiterated by tech giants time and again. This isn’t without merit. No industry or function has been left untouched by big data – be it a humble resume builder in the HR domain, the trucking industry, fast food services…one can go on and on.

With the whole world going digital, there is data about everyone and everything waiting to be exploited. Everything we say or do online is being leveraged. One industry that has come to rely on big data to progress is the retail industry.

What the customer wants is the one thing the retailer needs to know to stay ahead in the game and big data has made it extremely easy for retailers to gain an insight into the conscience of their customers.

Although there is a debate over the ethics of using personal data, the fact remains that not using it will cost the retailers heavily. So for the time being, ethics aside, big data is going to grow exponentially and retailers are going to hop on this train to provide personalized service to their customers.

If you want to add any other benefit that big data provides to the retail sector, mention in the comment section.

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