Anodot > Case Studies > AI-Powered Business Monitoring: A Case Study on PUMA and Anodot

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

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 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.

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

The implementation of Anodot's AI-powered business monitoring solution provided PUMA with unprecedented insights into their business. By dicing data into multiple dimensions, problems that weren’t known and trends that no one had ever seen became crystal clear. This eliminated the need for guessing invisible trends or wasting time trying to understand the root cause of a drop in a static dashboard. Furthermore, Anodot's metric correlations tool helped PUMA understand their business from a perspective never seen before. In the future, PUMA plans to add more use cases, such as customer experience, by measuring the processing time of the website, and work on ads effectiveness by measuring the logins from ads worldwide.

Quantitative Benefit

Anodot's system can connect to any data source in 3-4 minutes.
The average onboarding process with Anodot takes up to 6 weeks.
Anodot expanded PUMA's view to a much broader metrics than just revenue, including transactions per minute, items per transaction, conversion rate, items added to the cart, and number of returning customers.