Customer Company Size
Large Corporate
Region
- Europe
- America
Country
- Germany
- United States
- Canada
Product
- Sift
Tech Stack
- Machine Learning
- Device Fingerprinting
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Machine Learning
Applicable Functions
- Sales & Marketing
Use Cases
- Fraud Detection
Services
- Data Science Services
About The Customer
GetYourGuide is an online platform that connects travelers to experiences, helping their users to find and book attractions worldwide: museums, guided tours, day trips, and more. With over 30,000 attraction listings, some of the lowest prices in the industry, and fast and easy booking, GetYourGuide has become a top resource for tourists. GetYourGuide stands apart from other online booking sites with their dedication to an excellent customer experience, an expansive range of products, and a beautiful website. Although GetYourGuide is based in Germany and is founded on strong EU traffic, it has a huge user base in the US and Canada, and is focused on serving a rapidly expanding global market.
The Challenge
GetYourGuide, an online platform that connects travelers to experiences, was facing a significant increase in fraud as the range of attractions offered on the site and the number of daily transactions grew. Chargebacks from card-not-present fraud and fraudsters using last minute bookings for nonrefundable products began to impact GetYourGuide’s bottom line. To combat fraud, GetYourGuide’s lean team started manually reviewing suspicious transactions. But this cumbersome process did little to reduce their fraud, and chargebacks remained debilitatingly common. With GetYourGuide, customers had the ability to purchase tickets minutes before walking into an event; this miniscule window of time made scalable and efficient manual review impossible. Even worse, GetYourGuide’s imprecise system for flagging and blocking suspicious transactions produced a high false positive rate. Honest users, frustrated and inconvenienced by slow service, began to complain.
The Solution
GetYourGuide decided to implement Sift, impressed with the intuitive console and innovative machine learning solution. After the initial integration, GetYourGuide turned to Gianmichele Zappia to build the risk team and manage the fraud review process. The risk team found Sift to be extremely user friendly, and quickly became adept at using the console in just a matter of days. Once comfortable with the interface, they began sending custom data fields and retraining the algorithms to identify GetYourGuide’s unique fraud challenges. Within three months of using Sift, Gianmichele and his team were able to dramatically reduce the fraud on GetYourGuide. GetYourGuide’s fraud analysts were no longer overwhelmed by endless manual review, as automation using Sift Scores increased the efficiency of their workflow. Sift’s device fingerprinting proved especially helpful, as it made it easier for Gianmichele and his team of fraud analysts to catch repeat offenders who attempted to thwart previous blocks. Once Sift began flagging transactions as bad, GetYourGuide could easily pinpoint networks of bad users who were linked to that transaction.
Operational Impact
Quantitative Benefit
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