Analytics Big Data Case Study

How E-Commerce is Using Big Data to Improve Business? [Big Data Ecommerce Case Studies]

Big Data is very broad term in the data analytics world. There are several successful big data ECommerce case studies which proof the importance.

Many big unicorns are using big data and Hadoop to understand the behavior of their customers and increase sales. But knowing the behavior of your customers is not that easy. There are many challenges like data analysis, search, curation, storage, visualization, and privacy.

Big Data Ecommerce Case StudiesBut companies who have implemented big data or using data to analyze the customer behavior, sales and market perception are doing amazingly well. The below successful big data ecommerce case studies show how Ecommerce industry are using Big Data, Hadoop, Machine Learning, and Analytics to scale the business.

Before moving ahead, let’s see some of the interesting and helpful facts about Big Data in the ecommerce industry.

10 Amazing Big Data Ecommerce Facts & Figures

  • More than 91% marketing leaders believe companies take a decision based on the customer data. [Source: iab.net]
  • 85% of large corporates are using social media to drive as a marketing tool. [Source: iab.net]
  • But the sad part is 39% of marketers say they can’t turn their data into actionable insight. This is the sad part of big data. [Source: iab.net]
  • 86% customers are ready to pay more to get better customer experience. [source: lunch pail]
  • 87% marketing managers agree to the fact that right data is at most required to measure the ROI in their own company effectively.
  • Companies are successfully saving 25% budget on ads by optimizing their media inventory. [source: vemployee]
  • When Amazon implemented “Customers who bought this item also bought” recommendation feature, it had increased its sales by nearly 29%. [source: Fortune]
  • Magaseek, Japanese’s top fashion retailer, increased its revenue by ¥40 million with optimization brought in through Analytics. [source: vemployee]
  • Close to 70% users on Social media buy bases recommendations from others and another statistic says that upwards of 40% of users who give a positive review on social media purchase a product. [Source: Quora]
  • 54% of the survey says big data has brought gains in multi-channels sales. [source: Wipro]

20 Big Data Ecommerce Case Studies to understand use of Big Data in Ecommerce sector

Here are some of the most successful case studies in ecommerce and retail industry which will inspire you to use data even more correctly. These companies are the market leaders in their niche and have reported some huge profit in business after using big data.

Let’s start with the Big Data case ecommerce case studies and few big data retail case studies where big data is providing ROI.

Alibaba Big Data Case Study

This China-based billion dollar Ecommerce Company and world’s largest retailer has revealed how big data has helped them to increase the revenue. It has also helped them to use the data in the offline sector and another retail sector to grow the business.

According to Danfeng Li (Alibaba’s director of big data and technologies), Alibaba’s various properties hold about 80% of China’s PC, internet and app data, which it can integrate with first-party data to create singularly powerful data models.

According to the report by Reuters, the number of mobile-first users have been increased to 42% and has reached to 410 Million. This accounts for the total of 73% GMV. Check this WARC report for more details.

Aetna Big Data Case Study

AETNA is one of the largest healthcare insurance company of USA. Especially after the merger of Aetna and Humana, they have become one of the top healthcare, insurance and Wellness Company.

With around 19 Million customers, Aetna is using big data to improve the health and diagnostic of their clients.

After looking at the patients’ metabolic syndrome-detecting tests assesses patient risk factors, patient risk factors, company is focusing on finding the top factors which will impact the patient’s health most.

These data will help 90% of patients who doesn’t have a previous record, and 60% patients will increase the adherence.

General Electric (GE) Big Data Case Study

GE which is mainly known for their consumer-centric business like jet engines, oil & gas plants, and several such products.

But the industry was surprised when they launched one ad where one guy says “he got the job in software and will write code using which machine will communicate in GE”. Here is the video ad.

In late 2011, GE made an intelligent move by bringing William Ruh from Cisco Systems to start the Big Data system in GE.

In 2012, GE CEO Jeffrey Immelt announced to invest USD 1 Billion in the Big Data & Analytics segments over a period of four years.

GE collects the significant data from their jet engines, turbines, trains, and medical equipment and analyzes those to enhance the business and consumer lifestyle.

Here is a simple calculation by HP as per the details shared by GE. One of their gas turbines generates 500 GB of data. So with 12000 turbines will produce the below amount of data.

GE Big Data Case StudyWith this GE estimates, data can boost productivity in the USA by 1.5%, which will save enough money to raise the average income of citizen by 30% over a period of 20 years.

Kroger Big Data Case Study

Kroger is making use of big data through its joint venture with Dunnhumby. They collect, manage and analyze the data from their 770 Million consumers.

Claiming 95% of sales are rung up on the loyalty card, Kroger sees an impact from its award-winning loyalty program through close to 60% redemption rates and over $12 billion in incremental revenue by using big data and analytics since 2005.

Amazon Big Data Case Study

You can find plenty of Amazon big data use cases on the internet. Even Amazon is known for the Datasets for Hadoop practice.

Amazon is an ideal example in ecommerce industry as for how big data can be used to scale the sales. For Amazon, customer satisfaction is more important than the sales or figures.

Amazon is using the data to personalize your interaction, predicting trends and improving customer experience.

As stated above, Amazon found around 30% increase in sales after adding the below section based on the shopping experience of other users for the same product.

Amazon Big Data Case StudyWalmart Big Data Case Study

This mega retail company introduced semantic data in their search platform which improved online shoppers completing a purchase by 10% to 15%. In Wal-Mart terms, that is billions of dollars.

It was the mid of 2012 when Walmart announced the addition of Polaris, an in-house designed product to enhance the machine learning experience to their search engine. And the result of it is to the world now.

American Express (AMEX & AIG) Big Data Case Study

Amex started looking at the historical transactions with 115 variables to forecast potential churn in the Australian market. And as a result, they are now able to know the 24% accounts which will get closed in next four months.

Isn’t four months sufficient to retain the customer?

Also, American International group (AIG) is taking help of big data and visualization tools to predict and stop fraud well in advance.

eBay Big Data Case Study

eBay is using big data to provide better personalization and customer experience to the users.

Their system now handles final data velocity with 6 billion writes and 5 billion reads daily. The amount of data stored: 250 TBs.

eBay Big Data Case StudyGroupon Big Data Case Study

If you do online shopping, then you must have come across coupons websites like Zoutons, Groupon, etc.

Groupon is also using Big Data Hadoop to leverage the most out of it. It collects the data from both ecommerce companies and users to make daily deal transactions seamless.

Groupon is using Cloudera Hadoop system for the infrastructure and analysis of data on a large scale.

CVS Big Data Case Study

Every day over 5 Million customers walks into the CVS stores.

Like many other retail companies, CVS is also collecting and analyzing as much data about its customers’ habits as it can.

The entire industry is mining information to understand what people want and how to get them to want more.

CVS has a 15-year-old loyalty program called ExtraCare, and about 70 million people have used the card in the last six months. Personalized offers have been a focus for the chain: last holiday season it sent 117 million personalized offers, mostly through printouts on the bottom of receipts, up 72 percent from the previous year.

McDonald’s Big Data Case Study

McDonald is one of the world’s largest food chain with over 34000 local restaurants serving 69 million people in 118 countries each day.

Their daily traffic is around 69 Million and sells around 75 burgers every second. With annual revenue of around $27 Billion and an employee strength of 750k, how can they use big data to make the customer experience better and increase sales?

McDonalds is majorly using big data to optimize the drive-thru experience. The company mainly focuses on the following three factors while making an experience better-

  • Design of the drive-thru
  • Information that is provided to the customer during the drive-thru and
  • The people waiting in line to order at a drive-thru

And the results have been phenomenal with this implementation.

Wrapping Up

These were some of the great Big Data ecommerce case studies. Almost all the big companies have started using big data to personalize the user experience, to make the customer experience better and in return to increase the sales & business.

You can also check Hadoop Use Cases in Education and Big Data Use Cases in Banking and Financial Services for some more Hadoop Case Studies.

Here is an infographic showing how big data is impacting in a positive way in the retail sector by Wipro.

4 Comments

  • I loved your take on big data in e-commerce. Your article covered all the touch points and was very well written. This topic is of a lot of interest to me.

  • Great read, big data combines and processes all the tools related to utilizing large data sets, with the help of this business organisations can use analytics and figure out the most valuable customers.It helps businesses to create new experiences, services and products.

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