There’s nothing like watching your favorite sports team live and in-person. The roar of the crowd. The smell of the concession stand. The suspense of the game clock winding down to its final seconds. But would you have guessed that behind every ticket purchase, box of cracker jacks, and Jumbotron moment, there are teams of data professionals working to make your fan experience even more seamless and engaging?Joining Cindi today to discuss the data and analytics powering our favorite sports events are Jay Riola, the SVP of Strategy & Innovation for the Orlando Magic, and Charlie Shin, the VP of Data Strategy and Analytics for the Indianapolis Colts. With perspectives from both the NBA and the NFL, Jay and Charlie explore the evolution of mobile ticketing, challenges with identity management, the importance of building fan trust, and the most surprising insights they’ve ever discovered within their data. Key TakeawaysCustomers expect more for their data: When customers share their data, they expect something in return. Respecting their privacy and keeping their data safe are the bare minimum. They expect real, tangible value. As a business, your responsibility is to use this data to enhance their experience. Whether that be through custom offers, more relevant content recommendations, or more seamless purchasing experiences, what matters most is that you’re delivering on the expectation of value.Collecting data is one thing, putting it together is another: While technologies like mobile payments and social media have made it easier for businesses to collect data, they’ve also added complexity to the process of building accurate customer profiles. To truly understand the person on the other side of the screen, you must have the right skills and infrastructure to bring all that data together. Great data scientists need to be a triple threat: It is no longer enough to be very good at the technical components of your job and “so-so” at translating insights into actionable recommendations for business stakeholders. The best data scientists have technical chops, a deep understanding of how their business works, and the storytelling skills to turn insights into influence.Key QuotesCharlie:“In sports, they started off by focusing on the product, which is the on-field performance, our players. So a lot of the emphasis was using datas to optimize their investments, enhance their quality of on-field performance. But as the competition grew… now we've seen a shift where the focus is more on the customers and their experience in addition to the on-field quality.”“Identity management is a key topic in sports at this point… We have a variety of different data sources, whether it's ticketing, merchandising, digital engagement, or website or apps, there's a lot of information that's coming through. And then we're trying to figure out how do we tie all this together so that we have that clear understanding of that single view of our customers across these touchpoints. And I don't think this is just a sports industry challenge, right? I think it's a challenge across all industries that manage consumer information.”Jay:“We were a pretty early adopter of variable ticket pricing and thinking about the value from a ticket perspective of our games differently based on the team that we were playing, the time of the year, whether it was early in the season versus later in the season, obviously weekday versus weekend, but just recognizing that the marketplace values these games differently and so should we... Then it became, how do we dynamically price our tickets? How are we changing pricing as we approach games to reflect the demand situation that we have or if an opponent is performing better or worse than we expected, and we can raise or lower pricing. I think where data is really helping guide us… is product development and thinking about ticketing in new and kind of transformational ways.”“We have seen significant growth in ticketing revenue and imp