How Atom Tickets maintains secure, seamless ticketing
50%+
Reduction in chargebacks
$20-30k
A month in chargeback losses prevented
Days
Of manual review each week eliminated
OVERVIEW
Going to the movies has never been simpler
Atom Tickets reimagines the most convenient way for users to plan a night out at the movies and preorder concessions. The free app and website provide relevant reviews, trailers, and synopses to help moviegoers make the best decision on what to see. Atom users can quickly select the movie, theater, showtime, and seats, and after purchasing tickets they can invite friends and Atom will share the selected showtime and seats with them. At the theater, users skip the box office lines and go right to the ticket attendants, who scan a QR code on the user’s phone or Apple Watch to redeem their order. With millions of users on the platform, Atom Tickets operates in the US and Canada and is enabled on 22,000 screens.
CHALLENGE
A one-man fraud prevention operation
Atom Tickets was struggling with chargebacks; their chargeback rate was very high, which decreased their revenue and order volume. There isn’t a team focused on preventing fraud–while there are stakeholders across departments, fraud is a one-man army led by Trust & Safety Specialist Aaron Rennell. Managing all of Atom Tickets’ fraud was already a big job but it got even trickier for Aaron when Atom Tickets experienced spikes in activity during blockbuster movie ticket sales. The significant increase in online movie sales for the company also brought in an uptick in fraudulent purchases for blockbuster must-see movies. Given the increase in potentially fraudulent purposes, they needed a solution that would automate and streamline fraud prevention to make it manageable, and help them greatly reduce their chargeback rate.
SOLUTION
Game-changing automation and insights
On a recommendation from an industry peer, the head of product at Atom Tickets turned to Sift for a solution. Once they implemented Sift Payment Protection, it took only a few weeks for the model to start yielding powerful results. Within a month, their chargeback rate decreased significantly. Workflows were also set up to automatically block users with a certain Sift Score, which worked well in tandem with rules that Atom Tickets had also set up within Sift.
Aaron found Sift Insights (reporting capabilities) integral to his investigations; utilizing the Explore feature, he could view all ticket sales by Sift Score (risk score) and make bulk decisions—a task that previously would have required dropping data into a spreadsheet and reviewing accounts one by one, taking days to complete. This saved Aaron a massive amount of time when quickly dealing with large spikes in ticket sales. And with Roles and Permissions, he was able to see which users across departments were in review queues.
RESULTS
Keeping fraudsters off-platform, keeping revenue high
Since implementing Sift, Atom Tickets’ chargeback rate has decreased by more than 50% and continues to decline. They’re also preventing between $20-30k a month in chargeback losses, and cutting out a couple of days worth of work a week that would’ve been spent on manual review without Sift.
False positives are nearly nonexistent, particularly because Sift Insights helped Aaron understand what to expect from large spikes in activity and the model has been trained to know exactly what is fraudulent—and what isn’t. That accuracy means Sift requires little maintenance, and Aaron is able to manage fraud on his own, even as Atom Tickets continues to grow.
