Retaining professional basketball season ticket holders isn’t always a slam dunk. But by tying predictive models to marketing for those die-hard fans that make up the backbone of attendance, Anthony Perez has been able to direct targeted customer outreach and set the court for more analytics to come.
Last season, Perez and his team of three full-timers and an intern built a predictive analytics model for ticketing that factors in tenure, utilization of tickets, resale of seats and input from customer satisfaction surveys taken throughout the year.
From that, the team divided accounts as likely to renew, unlikely to renew or “fence sitters” and aimed its marketing attention where it was more urgent instead of en masse. The team was able to re-sign 87 percent of its season ticket holders, on par with NBA expectations, including higher than usual returns from fence sitters (65 percent) and “unlikely” (45 percent), in large part from the retention model that figured into personalized season ticket interactions and offers.
“During the season, if we see a season ticket holder whose tickets are going completely unused, we’re reaching out the next day to see why they weren’t able to use those tickets and compiling best practices for how we can get them to the stadium or [help them sell] on the secondary markets,” says Perez, who has an MBA and has previously worked at Goldman Sachs. “It’s decisions like that that are now informed by analytics.”
And while superstar center Dwight Howard filled seats at the Magic’s Amway Center, the team was able to add a new layer to its predictive model to factor in concessions. Fans in Orlando scan their tickets at stands, which enables tracking of food and beverage sales and promotional offers that include bringing ice cream to the seats of fans who regularly buy the treat. It’s a “thank you” and was an extra bump in a strike-shortened season.
It’s also about understanding what the fan takes home. “That’s the next piece, gauging our fan’s experience at the game. It’s a greater view of why they bought and keep those tickets in the first place,” says Perez.
Quotable: “We’ve been successful with different people on different projects because we don’t sit down and start talking about regression models and coefficients. We really try to make it relevant and keep it simple. That is what’s really helped people embrace what we’re doing. A lot things that we’re doing are behind the scenes and quantitatively vigorous, but that’s not how we’re presenting it.”
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