Company: Coca-Cola, the world’s largest non-alcoholic beverage company that operates in more than 200 countries and territories.

Challenge: Coca-Cola wanted to optimize its inventory management and product placement by using AI to analyze the transaction data and customer behavior of its vending machines. The company also wanted to increase its sales and market share by using AI to offer personalized and relevant products and promotions to its customers.

Solution:

Coca-Cola used AI to develop a vending analytics platform that leverages machine learning and data analytics to deliver tailored and relevant suggestions and recommendations to its vending operators and customers. The company used two types of AI models: natural language processing (NLP) and machine learning.

• NLP: Coca-Cola used NLP to enable its customers to order products using voice, through a feature called Coca-Cola Freestyle. The NLP model was trained on a large corpus of beverage-related text, and it could understand and respond to natural language commands, such as “I want a cherry coke” or “surprise me”. The NLP model also used natural language generation (NLG) to create personalized messages and feedback for customers, such as “enjoy your drink” or “try this new flavor”.
• Machine learning: Coca-Cola used machine learning to enable its vending operators to optimize their inventory management and product placement, through a feature called HIVERY. The machine learning model was trained on a large dataset of vending transaction data, and it could analyze and predict the demand and supply of different products, locations, and seasons. The machine learning model also used data analytics to provide vending operators with insights and recommendations, such as best practices, benchmarks, and action plans.

Outcome:

The AI-enhanced vending analytics platform helped Coca-Cola improve its vending operations and customer satisfaction, as well as its business performance. Some of the benefits were:

• Increased vending efficiency: The AI-enabled inventory management and product placement reduced the time and effort required for restocking and replenishing the vending machines. The AI system also reduced the errors and inconsistencies that often occur in manual and repetitive tasks.
• Increased vending quality: The AI-enabled inventory management and product placement improved the accuracy and reliability of the product availability and freshness, resulting in more satisfied and loyal customers. The AI system also improved the compliance and security of the vending machines, reducing the exposure to legal and regulatory risks.
• Enhanced vending value: The AI-enabled voice ordering and product personalization provided customers with a more convenient and engaging vending experience, making them feel valued and understood. The AI system also provided customers with more innovative and value-added products and promotions, such as new flavors, combinations, and discounts.

Conclusion:

This case study shows how a non-alcoholic beverage company, like Coca-Cola, used AI to develop a vending analytics platform that optimizes and enhances various aspects of vending for its vending operators and customers. By using AI, Coca-Cola was able to optimize its inventory management and product placement, by offering faster, easier, and more convenient ways to order products, using voice, through its vending machines. Coca-Cola not only improved its vending operations and customer satisfaction, but also increased its sales and market share by using AI to offer personalized and relevant products and promotions to its customers.

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

• The Story of Coca-Cola and its AI-powered Vending Machines
• How, why AI is driving innovative vending operations
• Artificial Intelligence at Coca-Cola – Two Current Use-Cases