Case Studies GiftCard.com Saves 25 Percent in Seasonal Compute Costs with Help from New Relic
Edit This Case Study Record

GiftCard.com Saves 25 Percent in Seasonal Compute Costs with Help from New Relic

Application Infrastructure & Middleware - API Integration & Management
Infrastructure as a Service (IaaS) - Cloud Computing
E-Commerce
Retail
Business Operation
Sales & Marketing
Supply Chain Visibility
Cloud Planning, Design & Implementation Services
Data Science Services
GiftCard.com was on a very aggressive growth path, experiencing 100 percent year-over-year growth from 2011 to 2012. This growth presented a serious challenge from an IT perspective, especially considering that the company does a large percentage of its business during the year-end holidays. The company was concerned about scaling to meet anticipated demand during the final quarter of 2012. A few key performance issues were the source of particular concern. Customers often call 1-800-GIFT CARD® to make orders, and the speed of the admin website was having an impact on the overall customer experience. Having slow admin systems means that customers need to stay on the phone longer. For years, the IT team had heard complaints about the speed of admin screens — the average load time was around eight seconds — but they couldn’t identify the source of the problem.
Read More
Founded in 2004, GiftCard.com is the largest online store focused solely on gift cards, with hundreds of brands and thousands of designs available to its fast-growing customer base. The company’s philosophy is that a gift card should be as unique as the individual receiving it, giving users the freedom to customize retail gift cards, prepaid Visa cards and e-gift cards deliverable by email or text message. GiftCard.com is PCI-compliant and boasts a stellar A+ rating from the Better Business Bureau. The company is a division of CardLab, Inc., a leading provider of prepaid card programs including IncentiveCardLab.com, PrepaidCardLab.com, Buxx.com and PAYjr.com. GiftCard.com has a core DevOps team in its Dallas headquarters, supported by a large remote IT staff. The company’s environment is built on a massive service-oriented architecture (SOA), with consumer and admin sites running .NET on Amazon Web Services (AWS). Web content management is in Kentico CMS. Some of the company’s smaller sites are written in PHP and serviced by REST APIs.
Read More
Winfield took a close look at the available options and New Relic quickly emerged as the one to beat. His team installed the New Relic web agent in October 2012. The software was up and running in 10 minutes and deployment of the New Relic server monitor quickly followed. GiftCard.com now runs New Relic on all public-facing and private internal machines to monitor admin sites, Windows Communication Foundation (WCF) service-layer sites, and external APIs used by third-party developers. With New Relic, the GiftCard.com IT team is able to drill all the way down to the most problematic screens. Then they use the New Relic API to record specific data for each web transaction, configuring the API to store the order number, customer information and account management data. With that information on each web transaction, Winfield and his team are able to track down orders at a much more detailed level than ever before.
Read More
GiftCard.com quadrupled the number of machines in use during the holiday season from 2011 to 2012.
The company managed to reduce response time in a number of key areas. For example, some customers were experiencing problems in checkout, with certain calls taking as long as four minutes. New Relic helped Winfield identify the source of the problem and get those calls down to 60 milliseconds.
The IT team succeeded in reducing the average response time on admin screens from eight seconds to one second. Not only did that improve the customer experience, but it also increased the number of calls the company could take while cutting per-minute phone costs.
Saved 25% in compute costs during holiday business spike by dropping CPU utilization from 80% to 60%
Reduced customer check out time by 35%
Moved to proactive performance management rather than learning of issues from customers
Download PDF Version
test test