Big Data Case Study on Walmart
- 1. Birla Vishvakarma Mahavidyalaya Engineering College Information Technology Department IT463 – Big Data Analytics Team Members: 1. 15IT006 - Jay Patel 2. 17IT431 - Nihar Desai 3. 17IT466 - Dhrumin Narola 4. 17IT467 - Jainam Parikh Faculty
- 2. A Case Study On WALMART
- 3. What is Big Data? � Big data is a term that describes the large volume of data - both structured and unstructured - that inundates a business on a day-to-day basis. � But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves. Why is Big Data Important? � The importance of big data doesn’t revolve around how much data you have, but what you do with it. � You can take data from any source and analyze it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smart decision making.
- 4. What is WALMART? ● Walmart is an American multinational retail corporation that operates a chain of hypermarkets, discount department stores, and grocery stores from United States.
- 5. How Walmart Operates and Dominates the Market? ● Walmart continues to offer very low prices and this is possible due to: 1. Its huge volume of sales that's possible due to the spread of its operation and its wide customer base. 2. A supply chain management system that maximizes efficiencies and reduces outlays. 3. Minimization of overhead and operational costs. ● Walmart has been able to capture a huge market share by selling almost everything and being almost everywhere. ● Walmart has a supply chain system that is regarded in multiple quarters as one of the most technologically advanced and efficient. ● Information such as point-of-sales data, as well as warehouse inventory and real-time sales are all sent to, and stored in, a centralized database that is shared with suppliers who know when to ship more products.
- 6. How WALMART uses Big Data to increase their Sales every year?
- 7. ● 245 million customers visiting 10,900 stores and 10 active websites across globe. ● Walmart sees close to 300,000 social mentions every week. ● It has 2 million associates and approximately half a million associates hired every year. ● Walmart takes in approximately $36 million from across 4300 US stores every day. ● Walmart collects 2.5 petabytes of unstructured data from 1 million customers every hour. ● Walmart made a move from the experimental 10 node Hadoop cluster to a 250 node Hadoop cluster in 2012. Figures ● The analytics systems at Walmart analyse close to 100 million keywords on daily basis to optimize the bidding of each keyword. ● The analysis covers millions of products and 100’s of millions customers from different sources. ● Walmart observed a significant 10% to 15% increase in online sales for $1 billion in incremental revenue. ● Walmart Labs analyses every clickable action on Walmart.com like: 1. What consumers buy in-store and online? 2. What is trending on Twitter? etc. Usage of Big Data
- 8. How it’s done? ● Savings Catcher - An Application that alerts the customers whenever its neighbouring competitor reduces the cost of an item the customer already bought. The application then sends a gift voucher to the customer to compensate the price difference. ● A mapping application at Walmart uses Hadoop to maintain the most recent maps of 1000’s of Walmart stores across the globe. These maps specify the exact location where a small bar of soap resides in the widespread Walmart store. ● Walmart uses data mining to discover patterns in point of sales data. ● Data mining helps Walmart find patterns that can be used to provide product recommendations to users based on which products were bought together or which products were bought before the purchase of a particular product. ● Example - finding that Strawberry pop-tarts sales increased by 7 times before a Hurricane. After Walmart identified this association between Hurricane and Strawberry pop-tarts through data mining, it places all the Strawberry pop-tarts at the checkouts before a hurricane.
- 9. Social Media Big Data Solutions ● Social Media Data is unstructured, informal and generally ungrammatical. ● A big part of Walmart’s data driven decision are based on social media data- Facebook comments, Pinterest pins, Twitter Tweets, LinkedIn shares and so on. ● WalmartLabs is leveraging social media analytics to generate retail related big data insights. ● Social Genome is a big data analytics solution developed by WalmartLabs that analyses millions and billions of Facebook messages, tweets, YouTube videos, blog postings and more. ● Through the Social Genome analytics solution, Walmart is reaching customer or friends customers who tweet or mention something about the products of Walmart to inform them about the product and provide them special discount. ● For example, if the Social Genome identifies that a lady frequently tweets about movies, then when she tweets something like “I love Salt”, the social genome solution of Walmart is able to understand that the lady is referring to the popular Hollywood movie Salt and not the condiment salt.
- 10. Mobile Big Data Analytics Solutions ● More than half of the Walmart’s customers use Smartphones and among these 35% of the shoppers are adults which is close to 3/4 th of its overall customer base. ● Walmart is leveraging big data analysis to develop predictive capabilities on their mobile app. The mobile app generates a shopping list by analysing the data of what the customers and other purchase every week. ● Walmart’s mobile application consists of a shopping list that can tell customers the position of their wants and helps them by providing discounts to similar products on Walmart.com. ● Another way in which Walmart is harnessing the power of big data analysis is by leveraging analytics in real-time- when a customer actually enters the Walmart store. ● The geofencing feature of Walmart’s mobile app senses whenever a user enters the Walmart store in US. The app asks the user to enter into the “Store Mode”. ● The store mode of the mobile app helps users to scan QE codes for special discounts and offers on products they would like to buy.
- 11. Some Examples where Big Data Analytics helped WALMART ● Example 1: ❖ During Halloween, sales analysts were able to see in real-time that although a particular novelty cookie was very popular in most stores, there were two stores where it wasn’t selling at all. ❖ The alert allowed the situation to be quickly investigated, and it was found that a simple stocking oversight had led to the cookies not being put on the shelves. ❖ The company was able to then rectify the situation immediately, avoiding further lost sales. ● Example 2: Shopycat-Gift Recommendation Engine at Walmart ❖ Walmart’s Shopycat recommends gifts for friends based on the social data extracted from their Facebook profiles. ❖ The app also suggests friends for whom users must by gifts depending on the level of interaction with them. ❖ When people click on a suggested gift, Shopycat also tells why a particular gift was suggested.
- 12. Walmart Labs and Data Cafe ● With a growing awareness of how data could be used to understand their customers’ needs and provide them with the products they wanted to buy, Walmart established @WalmartLabs also known as Data Cafe. ● At the Cafe, the analytics team can monitor 200 streams of internal and external data in real time, including a 40-petabyte database of all the sales transactions in the previous weeks. ● Teams from any part of the business are invited to visit the Cafe with ´ their data problems, and work with the analysts to devise a solution. ● The Data Cafe system has led to a reduction in ´ the time it takes from a problem being spotted in the numbers to a solution being proposed from an average of two to three weeks down to around 20 minutes. ● The Data Cafe uses a constantly refreshed database consisting of ´ 200 billion rows of transactional data – and that only represents the most recent few weeks of business! ● On top of that it pulls in data from 200 other sources, including meteorological data, economic data, telecoms data, social media data, gas prices and a database of events taking place in the vicinity of Walmart stores.
- 13. Technologies Used by WALMART ● Data from across the chain’s stores, online divisions and corporate units are stored centrally on Hadoop (a distributed data storage and data management system). ● Spark and Cassandra, and languages including R and SAS are used to develop analytical applications.
- 14. Conclusion ● In conclusion, WalMart is the number one retailer in the USA and it also operates in many other countries all around the world and is moving into new countries as years pass by. ● In this era when the technologies are reaching out to new levels, Big Data is taking over the traditional method of managing and analyzing data. These technologies are constantly used to understand complex datasets in a matter of time with beautiful visual representations. ● Through observing the history of the company’s datasets, clearer ideas on the sales for the previous years was realized which will be very helpful to the company on its own. Additionally, seasonality trend and randomness and future forecasts will help to analyse sale drops which the companies can avoid by using a more focused and efficient tactics to minimize the sale drop and maximize the profit and remain in competition.
- 15. THANK YOU