Company: Walmart, the world’s largest retailer that operates a chain of hypermarkets, discount department stores, and grocery stores.

Challenge: Walmart wanted to improve its customer service and satisfaction by offering faster, easier, and more convenient ways to shop. The company also wanted to optimize its store operations and inventory management by using AI to automate and enhance various tasks and processes.

Solution:

Walmart used AI to create a smart and connected shopping experience for its customers and employees. The company used several types of AI models, such as natural language processing (NLP), computer vision, and machine learning.

• NLP: Walmart used NLP to enable customers to shop using voice, through a feature called Walmart Voice Order. The NLP model was trained on a large corpus of shopping-related text, and it could understand and respond to natural language commands, such as “add milk to my cart” or “check out”. The NLP model also used natural language generation (NLG) to create personalized messages and reminders for customers, such as “your order is ready for pickup” or “you might need more eggs”.
• Computer vision: Walmart used computer vision to enable customers to shop using images, through a feature called Scan & Go. The computer vision model was trained on a large dataset of product images, and it could recognize and identify different products, prices, and barcodes. The computer vision model also used image enhancement to improve the quality and clarity of the images.
• Machine learning: Walmart used machine learning to enable customers to shop using recommendations, through a feature called Walmart.com. The machine learning model was trained on a large dataset of customer data, and it could analyze and predict customer behavior, preferences, and needs. The machine learning model also used data analytics to provide customers with tailored offers and suggestions, based on their previous purchases and browsing history.

Outcome:

The AI-enhanced shopping experience helped Walmart improve its customer service and satisfaction, as well as its business performance. Some of the benefits were:

• Increased customer convenience: The AI-enabled shopping options gave customers more choices and flexibility to shop anytime, anywhere, and anyway they wanted, without any hassle or delay.
• Increased customer loyalty: The AI-enabled shopping options created a more personalized and relevant shopping experience for customers, making them feel valued and appreciated. The AI system also used data analytics to increase customer retention and lifetime value, by offering incentives and rewards to loyal customers.
• Enhanced store operations and inventory management: The AI-enabled shopping options helped Walmart optimize its store operations and inventory management, reducing instances of out-of-stock or overstock. The AI system also used data analytics to forecast demand and supply for different products, categories, and seasons, enabling Walmart to plan and purchase its inventory accordingly.

Conclusion:

This case study shows how a mall & superstore, like Walmart, used AI to create a smart and connected shopping experience for its customers and employees. By using AI, Walmart was able to offer faster, easier, and more convenient ways to shop, using voice, images, or recommendations, through various channels. Walmart not only improved its customer service and satisfaction, but also optimized its store operations and inventory management by using AI to analyze and match its inventory with its customer data.

If you want to learn more about AI in retail, you can check out these articles:

• Top 10 AI use cases in retail | Google Cloud Blog
• 10 Present and Future Use Cases – Emerj Artificial Intelligence Research
• AI-Powered Surveillance System for a Retail Giant – Infopulse