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Optimizing Coca-Cola's Vending Machine Sales with CARTO & Google BigQuery
Technology Category
- Analytics & Modeling - Machine Learning
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Equipment & Machinery
Applicable Functions
- Maintenance
- Sales & Marketing
Services
- Cloud Planning, Design & Implementation Services
- System Integration
The Challenge
Coca-Cola Bottlers Japan Inc. (CCBJI), the largest Coca-Cola bottling company in Asia, operates a network of over 700,000 vending machines across Japan. The company collects a vast amount of data regarding the overall sales performance of each machine and how individual products perform per machine and location. Historically, CCBJI had to extract the necessary data for analysis from the core system, build their own mechanism to create a data warehouse using ETL tools, and perform various analyses. The sheer size of the data being produced posed several challenges for the company. These included the length of time needed to return the results of a simple query and the complex maintenance of such a legacy system.
About The Customer
Coca-Cola Bottlers Japan Inc. (CCBJI) is the largest Coca-Cola bottling company in Asia and a leading player among over 250 Coca-Cola bottlers operating around the world. The company produces and supplies approximately 90% of the Coca-Cola system’s products in Japan to serve the needs of their customers and consumers spread widely across the country. With a network of over 700,000 vending machines across Japan, CCBJI collects a vast amount of data regarding the overall sales performance of each machine and how individual products perform per machine and location.
The Solution
To overcome these challenges, CCBJI built an analytics and machine learning platform as a layer on top of existing systems centered on Google Cloud BigQuery with results visualized using CARTO. This new platform allows them to use different types of data such as Points of Interest (POIs) and foot traffic data to understand gaps and opportunities in the network. They are also able to predict performance by location, providing insights to key stakeholders in sales, marketing, and operations. CARTO’s fully cloud-native platform enabled CCBJI to work natively with their spatial data in BigQuery. The Spatial Extension for BigQuery allows them to eliminate ETL complexity and scalability limits previously encountered with their legacy GIS system. The Data Science team at CCBJI can now search, visualize, and subscribe to thousands of relevant locations datasets through CARTO's Data Observatory with frictionless access to these data streams in BigQuery.
Operational Impact
Quantitative Benefit
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