AWS for M&E Blog

Ticketmaster optimizes add-on offers for fans with a unified, serverless data stream powered by AWS

For avid enthusiasts, seeing their favorite team, performer, or celebrity in person is the ultimate thrill. The journey to these experiences almost always begins with an online ticket purchase, and this is where Ticketmaster, the global ticket marketplace, delivers on its mission of creating seamless, personalized experiences that connect fans with the events and services they want. To deepen fan engagement, the company recently teamed up with Amazon Web Services (AWS) to build a new serverless data stream solution that lets it personalize the add-on offers presented to fans ­across the Ticketmaster platform, such as parking and VIP passes, associated merchandise, and more.

Image Courtesy of Ticketmaster

Through this collaboration, the company has already seen a double-digit lift in add-on revenue per transaction, measured via a comparison study between a control group and a treatment group presented with the new curated, personalized add-on experience. Commenting on the project’s success, Ticketmaster SVP of Global Technical Operations Brandon Ammann shared, “When we can present fans with offers that match their unique needs and preferences, it’s a huge win. They’re happier with the experience and more inclined to make additional purchases and re-engage with us. Our work with AWS uses machine learning to meet fans in new, more personalized ways that ultimately improve their experience navigating through the Ticketmaster website.”

With the new data stream in place, Ticketmaster can surface and externalize event add-on inventory for optimization at scale, whereas before, it managed add-ons using an internal data source that surfaced inventory in real-time response to traffic. The solution also expands Ticketmaster’s ability to integrate inventory externally, extending access for third-party partners and sales to other ticketing platforms and markets.

Today, the platform runs add-on inventory based on event triggers to inform machine learning and data analysis. Machine learning ensures fans receive a custom add-on experience at checkout, tailoring the volume, rank order, and design of add-ons presented to each fan’s identity, purchase history, and event context.

Under the hood

Ticketmaster and AWS first built the data stream solution as a centralized, serverless ecosystem extensible to multiple facets of the platform. The company recognized this approach would allow it to sell and advance add-ons beyond the checkout experience and across its offerings. From there, Ticketmaster and AWS used the data stream to test and scale machine learning optimization in phases. The teams first focused on ranking add-ons by relevancy for each customer, then reduced the number of options shown in the interest of fewer scrolls and shorter dwell times before customers proceeded to payment details. User interface, UX, design, and copy testing followed to differentiate the experience by fan.

Overall, the solution has helped Ticketmaster to be more nimble and unlocked the potential for new vendor partnerships spanning a range of markets, including the hospitality and retail sectors. Ammann explained, “With the new setup, we’re able to increase fan engagement, enhance site load speed, and minimize the risk of bugs, which is made far easier with AWS. We can handle as many as a million requests per second, protect against any negative impact on ticket conversion rate, and opt to externalize inventory in the future so that hotel, travel, and transportation brands and other services can offer relevant event add-ons to our customers through our ticketing experience.”

Image Courtesy of Ticketmaster

Ticketmaster built the data stream solution on the AWS Lambda serverless compute service and an event-driven architecture built on Amazon Managed Streaming for Apache Kafka (Amazon MSK), push notification technology Amazon Simple Notification Service (Amazon SNS), Amazon Simple Queue Service (Amazon SQS), and the Amazon Kinesis serverless streaming data service. These technologies enable upsell inventories to run on event triggers, invoking functions on demand and delivering metadata for processing to inform machine learning and data analysis. On the backend, Ticketmaster also uses Amazon Elastic Container Service (Amazon ECS), Amazon Relational Database Service (Amazon RDS), Amazon ElastiCache clusters, and Amazon API Gateway.

“We are a technology-forward organization that builds scalable services with the customer experience at the center, and AWS is our latest partner to help us carry out this mission,” concluded Ammann. “Working with AWS enhances our capabilities to do things better, faster, and more cost efficiently. We can address challenges strategically and are well-positioned to continue evolving our offering to deliver the best fan experience.”

To learn more about how AWS customers are personalizing fan experiences, check out:

Emily McKinzie

Emily McKinzie

Emily McKinzie is an Industry Marketing Manager at Amazon Web Services.