Walmart Leveraging Big Data to Improve Business Operations

Walmart is one of the largest retailers in the world, serving millions of customers every day. To improve customer experience and increase sales, Walmart turned to big data analytics. The company collects enormous data from millions of customers every hour, running into petabytes at any given time. Heterogeneity and non-intuitive nature of this humongous data make it hard to manage and uses various technologies to provide real-time data to internal customers and centralize data for effective use.

• Walmart has 10,622 stores and clubs across 24 countries as of 2023.
• There are 4,717 Walmart locations in the United States as of April 2023
• Walmart serves more than 37 million customers every day and more than 230 million customers every week.
• Walmart sells more than 75 million different products.
• Walmart generated a revenue of approximately $573 billion worldwide.
• $53,921 million worth of sales was generated by Walmart’s e-commerce.
• Walmart makes more than $1.5 billion daily.
• com owns 6.3% of the market share in the United States.
• International stores of Walmart generated net sales of $81.1 billion.
• There were 2.3 million associates appointed worldwide, and 1.6 million associates are in the United States.
• Walmart’s e-commerce increased by 74% during the pandemic.
• 8 million Visits were recorded on Walmart.com as of 2023.

Here are some key takeaways from Walmart’s big data analytics journey:

1. Big data analytics can improve operational efficiency: Walmart’s big data ecosystem processes multiple terabytes of new data and petabytes of historical data every day. By leveraging big data analytics, Walmart improved its operational efficiency and achieved a significant 10% to 15% increase in online sales for $1 billion in incremental revenue.
2. Social media and mobile big data analytics can help understand customer behavior: Walmart uses social media and mobile big data analytics to understand customer behavior and preferences. By analyzing social media data, Walmart can identify trends and respond to customer needs quickly. The company also uses mobile big data analytics to provide personalized recommendations to customers and improve their shopping experience.
3. Big data analytics can help optimize supply chain management: Walmart’s carts are equipped with sensors that collect data on inventory levels, product location, and customer behavior. By analyzing this data, Walmart can optimize its supply chain management and improve product availability.
4. Private cloud can provide secure and scalable big data solutions: Walmart’s Data Cafe is the world’s biggest private cloud, providing secure and scalable big data solutions to the company’s employees. The Data Cafe allows Walmart’s employees to access and analyze data quickly and easily, enabling them to make data-driven decisions.
5. Building AI for Efficiency: Walmart is using AI technology to improve the consumer experience by reducing friction across multiple data sources. It’s expected that AI will continue to shape the future of data and have an increasing impact on society. They use industry trending techniques of computer vision, natural language processing, deep learning and probabilistic graphical models to build recommendation systems, personalization systems and voice conversational platforms at scale.

Walmart’s big data analytics journey provides valuable insights into how big data can be leveraged to improve customer experience and increase sales. By analyzing data in real-time, Walmart was able to optimize its supply chain management, improve product availability, and provide personalized recommendations to customers. As big data continues to grow in importance, companies like Walmart will need to continue to innovate and leverage big data analytics to stay competitive in the market.