Pro basketball exec outdoes competitors in mining data
When people think of having a job in the National Basketball Association, they might not think of a data junkie.
But for Karlis Kezbers, the Oklahoma City Thunder’s director of business intelligence and ticket strategy, the whole game is about numbers. Kezbers’ background is in ticket sales and service, but he volunteered for the data-mining gig, believing “the future of the business is in data.”
• Embrace data others miss: “A lot of teams frown upon people reselling tickets, but we embrace it,” Kezbers says. His team even helps people pick the right price to sell tickets, and advises on how far in advance to list. “We proactively reach out to suggest that people lower or raise the price” on secondary markets, Kezbers says.
The reason? “It keeps the fan base — even the idea of attending 43 (basketball) games is almost impossible,” Kezbers says. If someone resells 10 tickets, that’s 10 new contacts for the team to attract, he adds. The team watches its platform through Ticketmaster for the resells, but also tracks StubHub, SeatGeek and other major sites.
'The future of business is in data.' Karlis Kezbers, Oklahoma City Thunder
• Use data to retarget: Three years ago, the Thunder would give its sales team all of the email addresses of people who bought tickets. Now it leverages analytics from what people clicked on in an email to retarget the customer. For example, the team sent one email blast to 10,000 email addresses and scored recipients based on how many times they opened the email and what they clicked on. They included offers for merchandise, tickets and a call-to-action to join the team’s database. Then, they sent the scores to the sales team to help them know which people to follow up with.
• Leverage look-alike modeling: Kezbers says the Thunder also uses analytics to make assumptions about people based on what section they sit in, their annual household income and how far away they live from the arena.
• Be open-minded: Kezbers says the first question he asks his team is, “How can we help you to make your job easier or more efficient?” The second, “If you could hire one more person, what would you have them do?” Then, he tries to find ways to have data help solve the problem.
• Use data to entertain loyal customers in unexpected ways: There are so many games that exist in sports now, it is difficult to maintain season ticket value, Kezbers says. The goal is to learn as much as possible about these people. Much like a hotel asks what floor or pillow a loyal customer may prefer, the Thunder asks customers about favorite bands, restaurants and hobbies. “We use that to make an experience,” Kezbers says, sending an outdoor away game watch party invitation to all people who indicated they like barbecue, as an example. It’s a nice way of showing people that we’re not selling or sitting on all of the data we are collecting, Kezbers adds.
• Embrace a youthful spirit: Data people do not need to be seasoned professionals. Kezbers says he’s been impressed by the amount of software and design knowledge college graduates have when entering the workforce. Some of the skills took Kezbers 15 years to learn.
• Work with local colleges and universities: The Thunder has had a lot of success partnering with an analytics club from the University of Oklahoma, according to Kezbers. The group is analyzing the team’s schedule, determining the difference in attendance, merchandise sales and beers sales from a Monday night game to a Sunday afternoon game. This data will help the team budget and will also be useful for vendors for staffing purposes, Kezbers says.
• Find opportunities to do more: Sports teams have only tapped the surface of the data they have access to, says Kezbers. Even though his team analyzes secondary sales, market research, competitors and social media activity, there is always more data to mine. Says Kezbers: “We are a couple years behind other industries like airlines or hotels.”