AI Case Study
Trek Bicycle reduces error rates in its website and bike sharing app services from 8-14% to <1% using machine learning to monitor anomalies in real-time
Trek Bicycle uses New Relic's platform to ensure users have no issues accessing their digital services which include a website, retail management system and bike-sharing service. The platform monitors how the features are working and system performance constantly and is able to identify issues quickly as well as help map the root cause.
Industry
Consumer Goods And Services
Entertainment And Sports
Project Overview
"As Trek began contemplating relaunching its consumer-facing website and migrating to the cloud, they wanted to move from legacy monitoring tools to a sophisticated solution that could aggregate data, do real-time reporting, send and receive alerts, evaluate application performance, and more.
The DevOps team at trekbikes.com deployed New Relic APM as the company prepared to migrate its consumer-facing website to the SAP Hybris e-commerce platform and its data center operations to the cloud using Microsoft Azure. Explains Trek Web Technologies Manager Jason Endres, 'With our older, more traditional monitoring tools, we knew if an application was unhealthy, but we had nothing to point us to where precisely in the application the problem was occurring. With New Relic, we were finally able to meet our deadlines because we were no longer wasting development cycles trying to fix problems that weren’t being dealt with efficiently.'
Ascend, the retail management system that Trek sells to independent retailers, is Installed at 1,200 brick-and-mortar locations as the point-of-sale system—which comprises a desktop application with hardware integration and runs on Microsoft Azure—provides a complete ecosystem for running retail operation.
New Relic has enabled monitoring the many web services that make up that ecosystem, especially as the organization was completing the process of migrating the system to Azure... developers and quality assurance folks have access to the same data—which is hugely helpful for the development process”
Reported Results
Results reported suggests:
* Reduced error rate from 8-14% down to 0.4%
* Accelerated development cycles
* Improved relationships with customers by providing more visibility into system performance
Technology
Function
Sales
Sales Operations
Background
Trek Bicycle Corporation is a bicycle and cycling product manufacturer based in Wisconsin, US.
Benefits
Data