7-ELEVEN Brings Key Promotions Insights IN-HOUSE
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Alteryx Server
Tech Stack
- Data Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Cost Savings
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Retail
Applicable Functions
- Sales & Marketing
Use Cases
- Predictive Replenishment
Services
- Data Science Services
About The Customer
7-Eleven is a multinational convenience store chain based in the United States. It operates, franchises, and licenses more than 68,000 stores in 17 countries. The company offers a range of products, including beverages, candy, prepared foods, dairy, deli, bakery, snacks, grocery, non-foods, gasoline, and alcohol. 7-Eleven is known for its iconic Slurpee, Big Gulp, and other proprietary products. The company was looking for a solution to bring all of their vendor data sources together into one output to get deeper insights into their promotions.
The Challenge
7-Eleven, a multinational convenience store chain, was seeking a solution that could be used by business users on a daily basis without much technical support. They needed to get results quickly to share with external business associates, and provide multiple capabilities at a marginal cost. The company wanted to bring all of their vendor data sources together into one output to get deeper insights into their promotions to see what’s working and what’s not.
The Solution
7-Eleven implemented Alteryx Server to bring all of their vendor data sources together into one output. This allowed them to get deeper insights into their promotions to see what’s working and what’s not. They also used the Server platform for sharing insights with their management teams. They were able to send them daily snapshots of reports that are running on an automated schedule. This justified the time savings they were getting. The implementation of Alteryx Server allowed 7-Eleven to do in-house analytics without needing to have an army of analysts.
Operational Impact
Quantitative Benefit
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