StubHub Taps into Big Data for Insight into Millions of Customers’ Ticket-Buying Patterns, Fraud Detection, and Optimized Ticket Prices

StubHub Taps into Big Data for Insight into Millions of Customers’ Ticket-Buying Patterns, Fraud Detection, and Optimized Ticket Prices

  • Oracle Customer:  StubHub
    Location:  San Francisco, California, United States
    Industry:  Media and Entertainment
    Video:   StubHub Creates a Safe Market with Oracle Advanced Analytics

    StubHub Creates a Safe Market with Oracle Advanced Analytics

    StubHub uses Oracle Advanced Analytics to understand its customers in its online marketplace. Analysis times are much shorter, setup was fast and easy, and data scientists like the integration of R with the data warehouse.


An eBay company, StubHub is the world’s largest ticket marketplace, enabling fans to buy and sell tickets to tens of thousands of sports, concert, theater, and other live-entertainment events. StubHub reinvented the ticket resale market in 2000 and continues to lead it through innovation.

The company’s unique online marketplace, dedicated solely to tickets, provides all fans the choice to buy or sell their tickets in a safe, convenient, and highly reliable environment. All transactions are processed and delivered by StubHub and backed by the company’s FanProtect Guarantee. Company partners include the San Francisco Giants and University of Texas, along with more than 60 teams in Major League Baseball, the National Basketball Association, National Hockey League, Major League Soccer, and National Collegiate Athletic Association, complemented with companies such as ESPN, AEG,, and Paciolan.




A word from StubHub

  • “Big data is having a tremendous impact on how we run our business. Oracle Database and its various options—including Oracle Advanced Analytics—combine high-performance data-mining functions with the open source R language to enable predictive analytics, data mining, text mining, statistical analysis, advanced numerical computations, and interactive graphics—all inside the database.” – Mike Barber, Senior Manager of Data Science, StubHub

  • Deploy a comprehensive platform for real-time analytics that delivers insight into key business subjects, such as churn prediction, product recommendations, and fraud alerting for the online fan-to-fan ticket marketplace’s customers
  • Drive company’s growth in the online sports, concert, theater, and other live-entertainment events ticket marketplace, which works with millions of customers
  • Process big data volumes efficiently and analyze them in near-real-time to provide necessary customer-product recommendations and customer service


  • Deployed Oracle Database options, including Oracle Advanced Analytics and Oracle Partitioning, to increase capacity to store information about millions of customers coming from more than 25 data sources, in a single data warehouse, ultimately enabling faster analysis and more informed decision-making throughout the online-ticket marketplace
  • Implemented Oracle Active Data Guard enabling full use of a disaster recovery site for efficient data analysis, as well as batch and real-time reporting
  • Enabled data scientists to work directly with customer-related data—such as ticket-purchasing history—inside the database, and to use database options to explore the data graphically, build and evaluate multiple data-mining models, and deploy predictions and insights throughout the enterprise—drastically improving StubHub’s agility and responsiveness
  • Developed highly targeted ticket promotional campaigns and offers by having the ability to calculate 180 million customers’ lifetime value (or propensity) instead of just 20,000 values at a time
  • Used Oracle R Enterprise component of Oracle Advanced Analytics—an Oracle Database option—to reduce a fraud issue by up to 90%

Why Oracle

“We considered solutions from several other vendors, but Oracle Database was a natural choice for us because it enabled us to run analytics at the data source. This capability, together with the integration of open source R with the database, ensured scalability and enabled near-real-time analytics capabilities,” said Yadong Chen, principal architect, data systems, StubHub. 

Implementation Process

StubHub implemented the Oracle solution in just nine months—from conception, to analytics model development, to go live.

“Today, we have a cohesive set of solutions for big data analysis that help us acquire the data we need, discover new insights, make improved business decisions, and scale associated information systems for ongoing analysis,” said Brian Motzer, principal database administrator, StubHub.