Big Data in Retail Industry [Case Studies] – Take your Business to Next Level
Big Data – The New Age of Retailing
Here’s a walkthrough to have an insight into how Big Data is transforming the Retail Industry. This will help you understand how Big Data these days is not only confined to the technological domain but is a weapon for retailers to connect to their customers in a significant manner.
Big Data in Retail Industry help retailers in predicting the demands of customers, personalizing the experience of customers, and most importantly, it helps retailers in improving their operational efficiency. Learn more about what is Big Data.
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Why retail companies using Big Data?
The adoption of Big Data by several retail channels has increased competitiveness in the market to a great extent. Retailers are now looking up to Big Data Analytics to have that extra competitive edge over others. They are rapidly adopting it so as to get better ways to reach the customers, understand what the customer needs, providing them with the best possible solution, ensuring customer satisfaction, etc.
Use of Big Data in Retail Industry
The use of big data in the retail industry is accelerating rapidly, and with it, the need for businesses to find the best use cases for the same.
Big Data use cases in Retail Industry
Here are some of the use cases of Big Data in Retail Industry:
- Personalizing customer experience
- Predicting demands
- Operational efficiency
- Customer journey analytics
1. Personalizing customer experience
The success of any business is solely based on how happy their customers are and how well they are being treated. A happy customer is the one who is loyal as well. Big Data provides retailers opportunities to enhance their customer experiences. Big Data Analytics will help retailers in anticipating a customer’s demand and therefore would empower them in taking effective and customer-centric decisions and thus personalizing their marketing based on consumer data. The sources of these shoppers’ data include websites, mobile applications, social media platforms, sensors, etc.
This will help retailers in achieving greater heights in the market and thus will increase the competition as well. Imagine being able to buy products that are customized exactly according to what we need. We as a consumer need what else? We love everything customized these days and that’s why Big Data is here for.
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Big Data Case Study – Personalized Customer Experience
a. The ChatBot Revolution
Let’s begin Big Data in Retail Case Study – Chatbot Revolution
Mall of America, Bloomington, Minnesota – The largest shopping complex in the Northern States is a host to 500+ retailers, 50+ restaurants, 14 movie theatres, 2 hotels, an indoor theme park, and a museum. With such a huge database of customers, it was quite tough for them to provide a personalized experience to every one of them. Then what helped them in providing a better experience to their customers? What made their lives easier? Obviously, Big Data. IBM provided them with a chatbot (a simple text messaging platform) named ELF to oblige their customers to steer through the vast mall. This chatbot helped them to understand the needs of their customers in a better way and thus helping them creating a superior personalized experience for the customers.
According to Accenture, “delivering a good shopping experience improves customer satisfaction, repeat purchases, customer loyalty, customer referrals, revenues and customer engagement”.
IBM and Accenture used Big Data for achieving their goals, you can also achieve your goals with Big Data Start Learning Big Data.
2. Predicting demands
Here comes the second use case of Big Data in retail – Demand Prediction in Retail Industry.
Being first to market with a product or service has many advantages and benefits – but it comes with many challenges as well. And Big Data gives you the flexibility to deal with both. To survive in this ever-advancing technological and social media world retailers are supposed to be a step ahead of the customers. If retailers lag behind the customers they will lose them. Through Big Data Analytics, retailers will be able to generate insights on customer habits which would help them in understanding their products and services which are most in-demand and the ones they should stop offering. It would also empower them to predict the next big thing in the retail industry and then fabricate new products according to the current trends in the market. In this way, Big Data in retail helps retailers in predicting the demands of consumers.
Big Data Case Study – Predicting Demand
A. Weather Forecast for Retail Industry – Bright and Sunny
Can you imagine a Weather Forecast helped a retail chain in increasing their sales? Curious? Here’s the amazing story.
The weather forecast is not just about the weather. It has much more to offer. A weather channel predicts the impact of weather on their viewers’ emotions.
One such example of Big Data Analytics in retail is the collaboration of Pantene, Walgreens, and The Weather Channel. The Weather Channel collected the data about the humidity level in the air and the time it will be highest. This helped Pantene and Walgreens to advertise their product relating it to the hair problems that a woman might face due to the increased humidity in the air. It then prompted women to seek out for a product at their local stores to prevent themselves from getting any kind of hair problems.
This resulted in a 10% increase in sales of Pantene at Walgreens for the month of July and August, along with an overall increase of 4% in sales across the entire hair category at Walgreens. This was branded as “hair cast” and trended on social media under the #haircast tag.
Know more about Real-Time Applications of Big Data in various sectors.
3. Operational efficiency
Efficiency across different channels within the retail firm is something that gives them the license to operate freely. Coordination between the inventory department and the production unit is something that is of the highest importance. Big Data in retail helps retailers monitor the store-level demand in real-time to ensure best-selling items remain in stock. It has come to the aid of dealing with faster product life cycles and ever-complex operations and thus helping them to understand supply chains and product distribution to reduce costs.
Big Data has facilitated them in dealing with intense pressure to optimize asset utilization, budgets, performance, and service quality. Servers, plant machinery, customer-owned appliances, energy grid infrastructure, and even product logs are few examples of assets that produce valuable data. This data increases rapidly with every passing day and collecting, preparing and analyzing this data is a hefty task.
How to deal with this data???
Obviously Big Data Analytics.
Scrutinize 10 best Big Data Analytics Tools with its uses.
4. Customer journey analytics
A zig-zag pattern on the Cardiac Monitoring Machine (a machine that continuously monitors the activities of your heart) indicates that there’s life. A customer’s journey is also the same. It is also a zig-zag pattern across different channels from research to purchase. And this is what indicates that there’s life in the market. Big Data is the ultimate tool to handle and analyze this journey. With the advancements in the technologies and the rise of social media, customers can have access to information about any product, anywhere and that too within seconds. Consumers these days are more empowered than ever before. Big Data will help retailers to perceive the most effective ways to reach them and compel them to purchase.
Big Data is like the cardiac machine that will help retailers to monitor the customer activities and thus will entitle them to improve the quality of customer experience.
Get a complete understanding of how Big Data is helping Flipkart to achieve the milestone
Big Data Case Study – Customer Journey Analytics
a. Retail – Faster than AirMail / Email
Let’s start reading the third case study of Big Data in Retail – Customer Journey Analytics.
Before the advent of Big Data, a customer was supposed to inform about his needs to the retailer personally. From the products that are out of stock to the products, he would need in the near future, each and everything was needed to be communicated to the retailer. And since Big Data has taken over the market, this experience has been entirely different.
In today’s world, there’s hardly anything that we don’t post on social media platforms. I was planning a family trip to Rajasthan, I posted about it on social media a week before showing my excitement for the trip. And just a day after that, I received a message from one of the retail chains that there is an ongoing offer on sunscreens and deodorants. I was clueless. Before I could even plan to go out and buy those things, they already know what are the must-have things that I would need on the trip. They are already aware of my trip and the weather conditions there. What more I could have asked for. What a turnaround Big Data has brought into our retailing experience.
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If these professionals can make a switch to Big Data, so can you:
Java → Big Data Consultant, JDA
PeopleSoft → Big Data Architect, Hexaware
In this ever-growing digital world, Big Data is everywhere. Almost everything we do online can be analyzed. Big Data is the future of Retail Industry and to survive and succeed in this ever-advancing digital world, customer insights are the biggest wealth retailers can ever have. If not exploited properly and on time, a retailer would stand to fall behind the rest of the pack. On the flipside, Big Data has endless advantages and can take your business to unimaginable heights.
The use of big data in the retail industry is astonishing. Big Data is growing endlessly.
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