New York-based SeatGeek is a ticket search engine that enables customers worldwide to search for, find, and purchase tickets to countless events from multiple sources – all in one spot. With 60% of SeatGeek’s traffic coming via mobile app (iOS, Android, and iPad) and mobile web traffic, and 40% by desktop, customers can find the most highly sought-after tickets to sporting events, live shows, theatrical performances, and more on one sortable and easily consumable platform.
Fraud management at SeatGeek used to be a shared responsibility within the Customer Service team, something that everyone pitched in on, but that no one truly owned. This incredibly time-consuming process was centered on an internal rules-based system, with Customer Service representatives manually vetting buyers and sellers by checking basic data points like billing address, shipping address, previous purchase history, and ticket price thresholds. Because this review was shared across the team, staying ahead of fraudsters was impossible and unscalable.
“ Sift Science is a holistic and well-rounded fraud solution – we can send any and all the data that we want, and we get back all of the actionable information that we wouldn’t have found on our own.”
SeatGeek’s integration of Sift Science was easy, with 1-2 engineers dedicated to the process. Once the solution was fully imbedded in their internal order management system – using Sift Science’s simple API webhook – the SeatGeek team focused on leveraging their new tool. Nicole Grazioso joined SeatGeek as the Payments & Risk Manager and was tasked with building a team, creating a fraud management process, and bringing down the chargeback rate. Nicole’s experience working in customer service and investigating suspicious behavior meant that she was well-equipped to focus on maintaining a customer-first purchasing experience while developing effective fraud workflows.
As Nicole’s fraud team grew from one to five, their first order of business was developing a method of programmatically reviewing orders specifically in Sift Science. Fraud management at SeatGeek is built upon the Sift Science solution, with payment abuse and content abuse both providing insights into how trustworthy a buyer or seller is. SeatGeek relies on Sift Scores to quickly and efficiently identify users’ riskiness, and this real-time information allows them to dynamically update checkout flows for buyers, depending on their likelihood of fraudulence.
SeatGeek has successfully lowered their chargeback rate to a manageable level. Even more valuable, however, is that they can now predict potential fraud fluctuations proactively. Nicole’s teams check users’ Sift Scores multiple times during the customer’s journey on the website or app. SeatGeek is continually sending more labels to Sift Science, and have come to see Lists as a very important part of what they do on a day-to-day basis, as well as the Analyze feature to track labeling, and measure effectiveness. In the average 30-day cycle, Sift Science saves SeatGeek over $600,000 in chargebacks, a hefty return on the low cost of the solution.
Most importantly, SeatGeek has found that Sift Science highlights the signals indicating a user is legitimate – not just fraud red flags – and that means that their team can quickly spot and reward good customers. Armed with that knowledge, SeatGeek treats known legitimate users as a white list. Just as they use a high score to auto-block suspicious users, SeatGeek looks at low-score users to determine who can speed through checkout. Dynamic buyer authentication and a flexible checkout flow keep good customers happy and increase conversions, which just goes to show how smart fraud management can also be smart for revenue growth.