US Foods Analyzes Transactions from 300,000 Customers with Snowflake and DataRobot
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Snowflake’s cloud data platform
- Snowflake Connector for Python
- DataRobot
Tech Stack
- Python
- Amazon S3
- SQL
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Infrastructure as a Service (IaaS) - Cloud Computing
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Food & Beverage
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Predictive Maintenance
- Supply Chain Visibility
Services
- Data Science Services
- Cloud Planning, Design & Implementation Services
About The Customer
US Foods is a food service distributor and one of America's largest food companies. The company is based in Rosemont, Illinois and has approximately 26,000 employees. US Foods provides an expansive catalog of food products, culinary equipment, supplies, and technology to approximately 300,000 restaurants and food service operators. The company uses data analytics and data science to monitor performance, predict churn rate, and accelerate growth.
The Challenge
US Foods, one of America's largest food companies, was facing significant challenges with its legacy, on-premises data warehouse. The system required constant maintenance, experienced frequent resource contention, and could not affordably store more than two years’ worth of data. Business analysts took weeks to prepare a single report due to the system’s counterintuitive user interface, inability to load large data sets, and limited BI features. Reporting delays led some business users to seek insights from siloed Microsoft Access databases and Excel spreadsheets. Data science modeling to predict customer loyalty and churn rate was simply impossible. US Foods evaluated several cloud data management solutions, but none offered the right mix of performance and affordability.
The Solution
US Foods adopted Snowflake’s cloud data platform, which scaled to become their single analytics repository for transaction data. The Snowflake Connector for Python and bulk loading from Amazon S3 enabled daily ingestion of large data sets without causing bottlenecks. Snowflake’s native support for SQL and clean, easy-to-navigate interface accelerated report creation. DataRobot integration enabled predictive analytics for churn rate that identified at-risk customers in need of proactive outreach by US Foods’ retention team. This solution provided a significant improvement in data management and predictive analytics capabilities for US Foods.
Operational Impact
Quantitative Benefit
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