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Data analytics applications let teams call new ticket-pricing plays

Professional sports teams are increasingly embracing analytics tools to help them implement dynamic pricing strategies designed to enable them to capture as much ticket revenue as possible.

It used to be that professional sports teams set ticket prices in stone at the beginning of the season and charged the same amounts game-to-game. But team and league officials eventually started to notice that tickets for some games were selling for dramatically higher prices on the secondary market. That led them to wonder if they were leaving money on the table.

Today, teams are increasingly adopting dynamic pricing strategies, which involve changing the price of tickets from one game to the next based on expected demand. They can charge higher prices when an archrival or a strong opponent comes to town and many fans want to see the game, and lower ones when the matchup is less exciting. And data analytics applications are playing an important role in enabling teams to do so.

"It's great to see that teams are starting to wake up to it and pushing the envelope a little bit," Peter Fader, a professor of marketing at the University of Pennsylvania, said at the 2015 MIT Sloan Sports Analytics Conference in Boston during a session on dynamic pricing.

The approach can pay off. Scott Jablonski, vice president of club business and analytics for the National Hockey League, said total revenue from ticket sales is up 27% among NHL teams since the 2009-2010 season, despite attendance increasing only 5% over the same period. He credited much of the increase in revenues to the growing use of dynamic pricing plans driven by analytics technologies.

Data analytics applications help sharpen edge on pricing

The NHL offers its teams access to a suite of analytics tools, primarily built in Tableau's business intelligence and data visualization software, that allow them to map out every seat in their arenas. For each game, they can view which seats belong to season ticket holders, which are still available to be sold, and how much seats are going for through ticket agencies and other resellers on the secondary market. Based on the data, teams can take action by adjusting prices up or down to stay competitive with secondary sellers and take better advantage of high demand or improve the perceived value of tickets to lesser games.

When I joined the industry eight years ago, I thought you just put a price on a ticket and you were good. You're not.
Scott Jablonskivice president of club business and analytics, NHL

New pricing approaches have become a trending topic among sports teams because of the growth of the secondary market for tickets. There was a time when a team's box office was pretty much the only game in town. But during the past decade, the prominence of secondary sellers exploded as agencies increasingly started buying up large blocks of tickets and selling the ones to in-demand games for high premiums. In addition, StubHub and other websites that let fans resell tickets have become big players, with many teams signing up as business partners. All the secondary sales give teams an opportunity to better peg their own ticket prices to what fans are actually willing to pay.

In some cases, though, teams are still working out how exactly to run dynamic pricing programs. At the MIT conference, Joseph Xu, a doctoral student in operations management at Penn, presented findings from a review he recently conducted of a Major League Baseball team's dynamic pricing efforts. His results showed that the strategy barely lifted the team's revenue at all compared to traditional ticket pricing.

Bad game plan: Shaking off data signs

The reason for the lack of tangible benefits, Xu found, wasn't because dynamic pricing failed in and of itself, but because team officials didn't take the actions the data was telling them to. For example, they never adjusted prices downward when demand dropped, something that happened often in the second half of the season he reviewed because the team performed poorly then. Xu said management refused to lower prices because it didn't want to alienate fans who had paid higher prices when they bought tickets further in advance -- but that meant the team was asking unreasonably high prices for games that offered relatively little value to fans. As a result, he added, many seats went unfilled.

Xu said the example shows how careful teams need to be when adopting dynamic pricing strategies: They can pay off, but only when implemented properly. "It's important to give it as much flexibility as possible," he said. "That's the whole point: You get to react to demand."

Used effectively, Jablonski said, data analytics applications can give teams greater insights into how different factors affect ticket sales -- and how to respond to those factors. And with how competitive ticket sales have become, he thinks a more dynamic approach on pricing is critical.

"When I joined the industry eight years ago," he said, "I thought you just put a price on a ticket and you were good. You're not."

Ed Burns is site editor of SearchBusinessAnalytics. Email him at eburns@techtarget.com and follow him on Twitter: @EdBurnsTT.

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This was last published in March 2015

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How big a change do you think teams' use of data analytics applications really is?
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I think it's an immense change. Prior to the rise of proper analytics, a lot of what teams did relied on guesswork and comments from customers who bothered to give feedback. Analytics, on the other hand, has made it easier than ever before to figure out what's actually happening, what works and what doesn't, and help us decide what to do in the future. It would be difficult to overstate the magnitude of this change.
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