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AI-Powered Business Monitoring: A Case Study on PUMA and Anodot
Technology Category
- Networks & Connectivity - NFC
- Sensors - Dimension & Displacement Sensors
Applicable Industries
- Equipment & Machinery
Applicable Functions
- Procurement
Use Cases
- Behavior & Emotion Tracking
- Time Sensitive Networking
Services
- System Integration
- Training
The Challenge
PUMA, a global eCommerce giant, was facing difficulties in monitoring all revenue aspects of their 45 eCommerce websites. They lacked a tool to distinguish what was normal or abnormal across their platforms. For instance, an issue with gift card purchases in Switzerland went unnoticed, which could have resulted in significant financial loss if discovered later. PUMA's Senior DevOps Manager, Michael Gaskin, was interested in Anodot based on the experience he had with another Anodot customer. He understood the challenges PUMA was facing and sought a solution to monitor their websites more effectively.
About The Customer
PUMA is a global eCommerce giant with 45 websites spanning multiple countries. They deal with a vast amount of data and transactions on a daily basis, making it challenging to monitor all revenue aspects of their websites. PUMA's Senior DevOps Manager, Michael Gaskin, recognized the need for a more effective monitoring tool to distinguish normal and abnormal patterns across their platforms. The company sought a solution that could provide a deep understanding of their business environment and needs, and help them achieve their business goals.
The Solution
Anodot, an AI-powered business monitoring solution, was implemented to address PUMA's challenges. The onboarding process with Anodot involved understanding the primary pain points of the customer, discovering the needed dimensions to measure, and building a diagram of the pain point. The data was then integrated into Anodot's system, which automatically started to analyze business data, finding seasonality behaviors and detecting anomalies. The customer received full training of the system, including how to see the data, find relevant anomalies, create new alerts, and tackle complex issues. The average onboarding process usually takes up to 6 weeks. With PUMA, Anodot integrated revenue measures first, but then expanded to broader metrics such as transactions per minute, items per transaction, conversion rate, items added to the cart, and number of returning customers.
Operational Impact
Quantitative Benefit
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