- Mobile and web-based ticketing search engine
- Over 60% mobile traffic
- Fraud in the form of chargebacks and content abuse
- High-value tickets require preventative and scalable fraud management
- Maintaining a seamless customer experience
- Switched from internal rules to machine learning
- Quick mobile and desktop integration and Sift Score-centered system
- API and webhook allow for easy access to investigation
- $600,000 in average monthly savings
- 60x ROI
- Made the review process 10x more efficient
A front-row seat in ticket sales
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.
This game-changing startup enables its users to view their options before continuing on to a quick and easy checkout process, which is essential for a smooth customer experience. In fact, SeatGeek’s focus on an excellent user experience sets them apart from the competition – their Deal Score gives buyers the power to find the best value for their dollar; their beautiful, interactive 3D maps allow buyers to effortlessly view available seats; and their cutting-edge apps enable easy searching, purchasing, and storing of tickets on smart devices.
Making ticket transactions more transparent
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.
Working with partner ticket sites and, increasingly, individual sellers on their marketplace, SeatGeek faces challenges on several fronts. Fraud – in the form of payment fraud and some content abuse – takes up precious time and resources. Additionally, by operating on mobile, SeatGeek must contend with sometimes conflicting geolocation signals, in-app purchases, as well as the buyer’s expectation of near-instantaneous delivery of tickets. Finally, when fraudsters aim for high-dollar-value events, the resulting chargebacks are expensive and damaging, so preventing fraudulent purchases is essential to the long-term health of the business. After SeatGeek’s chargeback rate hit an unacceptable high in early 2016, a cross-functional task force researched solution options and – upon recommendation from other ecommerce businesses – the team turned to Sift.
“The time that we spend in Sift labeling and investigating users has been received back in value.”
Workflows that fuel automation
SeatGeek’s integration of Sift was easy, with 1-2 engineers dedicated to the process. Once the solution was fully imbedded in their internal order management system – using Sift’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. Fraud management at SeatGeek is built upon the Sift 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.
“Sift has changed the way that we work internally and how the site works. We’ve begun to rely on the Sift Score programmatically, as well as within our workflow.”
Scoring high with fraud managers
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, 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 saves SeatGeek over $600,000 in chargebacks, a hefty return on the low cost of the solution.
Most importantly, SeatGeek has found that Sift 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.
“Having the data that we get out of Sift has been very valuable in terms of making smarter business decisions and planning out product rollouts.”