Group Created with Sketch.
Volume 22 No. 34
  • Created with Sketch.
  • Created with Sketch.
  • Created with Sketch.

Data tells the story

Inundated with information, sports organizations are changing how they digest and act on analytics.
Analyzing data can help teams identify the fans who fill their arenas and stadiums. That data also can generate ways to keep them coming back.
Photo: getty images

I

t’s been years since sports teams debated the need for investing in tech-driven data and analytics to better understand fans’ interest and buying habits. Now, it’s a given.

 

Today, discussions center more on what looks like a relentless arms race to collect as much information as possible as fast as possible.

And, as part of the rapid expansion in staffing and sophistication in front offices, there is also increasing emphasis to broaden the use of analytics. Marketing, sponsorship and stadium and arena operations are among the business categories most often explored and added to data-driven decision-making in recent years.

Beyond those basic parameters, there is plenty of room for varied approaches and investment — even within the affluent world of major league franchises.

Aaron LeValley, senior vice president of business operations and strategy with the Los Angeles Kings and parent company AEG, believes the constant craving for more and more data has reached a tipping point.

“Everybody wants to grab everything and what we do is end up doing that at 60% rather than focusing on 75% of that information and doing that at 100%,” he said, referring to manpower and resources being scattered by a glut of data to parse. “You know what, we can get involved in all these areas and we want to. But I don’t want us to do it half-assed.”

For that reason, LeValley predicts teams will soon start paring back on ever-sprawling data collection.

Or will they?

“It’s kind of a tough space because you never want to be caught where we have a lack of data and we cannot answer some really important questions,” said David Elgin, vice president of analytics for the Atlanta Hawks and State Farm Arena. “People like me, and with tools like data warehouses and [customer relationship management], you would definitely rather over-collect and only use 10% of it and keep 90% of it for a rainy day. The salient point is we’d love to collect every piece of data in the world.”

Managing constant floods of information and making sense of it to determine possible next steps will always be challenges.

At VenueNext, a company providing mobile app technology and support to tie together information from all aspects of arena and stadium operations, executives have seen firsthand the difficulties clients face to make the best and most use of data. The company counts the San Francisco 49ers and Levi’s Stadium, Churchill Downs, the Orlando Magic, New York Yankees and Minnesota Vikings among its clients.

Frank Conway, VenueNext chief product officer, said teams and other clients always respond enthusiastically when asked whether they want additional data. “What we would see is they didn’t have the capabilities to actually act on it. As a technology vendor, our responsibility has had to transition from, ‘We will give you the data and then you can figure out what to do with it’ to, ‘We need to be part of the solution to crafting the story about the data.’”

That realization is happening within the teams’ front offices, too. Data and analytics executives with a number of teams described a shift toward regular and frequent meetings with department heads to better learn what types of data and analysis can make a difference — and to brainstorm about other ways to look at the numbers to adapt to business trends.

Portland Trail Blazers executives Dewayne Hankins, the team’s chief marketing officer, and Mike Schumacher, director of business analytics, said collaboration improves as department leaders see the results of data analysis. Building credibility and rapport through experience is a must, they said.

“As people have seen [data-based recommendations] come back accurate, they want more help to solve problems that they may not be able to do on their own,” Schumacher said.

KAGR CEO Jessica Gelman sees how analytics can help teams make changes and improve the fan experience, but says it’s not as widespread as some may think.
Photo: Eric Adler

And, as time goes on, more people continue to climb the ladder in team executive ranks who have been immersed in data and analytics.

In many ways, sports teams have only just scratched the surface with data and analytics, said Jessica Gelman, CEO at Kraft Analytics Group, known as KAGR. Kraft Sports & Entertainment, owners of the NFL Patriots and MLS Revolution as well as Gillette Stadium, hired Gelman in 2002 on the business side. In 2006, Gelman co-founded the MIT Sloan Sports Analytics Conference — an obvious sign of her passion for data-driven business strategy. Eventually that led to creating KAGR, which not only provides data and analytics for the Kraft teams but consults for Ticketmaster, the NFL, On Location Experiences and Harris Blitzer Sports & Entertainment — which owns the Philadelphia 76ers, New Jersey Devils and Prudential Center — among others.

Gelman said the basics of pricing and who shows up and what their experience entails will always be important, as will the ability to glean more detailed information about each step in the process. This information drives changes to improve fan experiences. Beyond that foundation, which requires constant vigilance, she sees ample room to do more analytics to go with all of the existing analysis.

What’s the difference? “To me, analysis is really descriptive in nature,” she said. “How many season-ticket holders do I have, where do they sit, what is their game attendance? It’s more looking backwards and not turning it into predictive in terms of what steps can we take to try and improve any of the things we might be seeing. There’s some of it that’s happening with retention modeling and lead scoring and some stuff, but it’s not as pervasive as you might think.”

■  ■  ■  ■

Selling more tickets and pricing them more effectively kick-started the shift toward teams building data warehouses and creating data and analytics departments in the first place. Tickets remain the lifeblood of teams’ local revenue, so it’s a sure thing that the quest for more incremental gains in ticketing will continue as long as spectator sports exist.

Where the challenge comes in is when deciding what the mix should be between tickets and everything else: retail, concessions, social media and messaging, venue operations, esports ventures and more.

Sports teams, generally speaking, can’t build internal data and analytics departments anywhere near the size and scope of, say, major airlines, hotels and other consumer businesses responsible for both setting and meeting similar expectations for personalized content and offers.

To narrow the gap, teams turn to sponsors and vendors for shared data. And major software and business consulting firms are involved in partnerships with leagues and teams to collect and analyze customer and sponsor data. One example would be the Golden State Warriors, who have turned to Accenture, Adobe, Google Cloud and SAP, among others, for help with data and analytics. 

All of this data generation and collection brings back the quandary of finding newer and better ways to consider the information and use it.

“Every day I’m thinking about how do we take data and leverage it into insights that are going to support decisions made by our key executives,” said Ian Hillman, vice president of strategy at Harris Blitzer Sports & Entertainment. His colleague, Sixers Chief Marketing Officer Katie O’Reilly, shared the sentiment, noting the NBA team tries “to use data to drive every single decision we make.” That goes well beyond ticket inventory and prices to what messages are sent on social media and in marketing emails, what goes into scripts for promotions and what’s included in game entertainment. 

Seemingly everything can be, and is, measured by teams. The Golden State Warriors several years ago began monitoring decibel levels at Oracle Arena to measure what fans like most during games — from T-shirt tosses and dance team performances to Stephen Curry hitting a 3-pointer.

“Is there a scientific way where we can measure fans’ reactions to what we do?” said Brandon Schneider, Warriors chief revenue officer. Measuring crowd reaction could take the guesswork out of in-game entertainment and promotions.

Chris Kamke, vice president of strategy and analytics with the Tampa Bay Lightning, said his department grew to seven people from three over the past few years, largely because of the success of using data to drive decisions — and a desire by various departments within the organization to develop strategy using a foundation of numbers-based evidence.

“Everyone is going to have their own priorities and their own challenges,” Kamke said. “We have made the decision to do as much stuff internally rather than to contract with third parties. That doesn’t mean that’s the right answer; it’s the answer we’ve chosen.”

Teams and vendors almost unanimously declined to disclose how much it costs to build up analytics capability and hire researchers and strategists capable of evolving as the tech world hurtles forward. Department sizes often range from a handful of people to 10 to 15 at the upper end.

Jay Riola, the Orlando Magic’s senior vice president of strategy, said the NBA franchise “has spent several million” dollars on data and analytics, customer relationship management and marketing automation software, hardware and systems since the team moved into its current arena in 2010.

Riola said the timing was perfect for the arrival of Amway Center because it came just as the secondary ticket market dramatically expanded online and as smartphones proliferated as the preferred way for people to shop and pay for all kinds of things, including sports and entertainment. Magic executives had the foresight to invest in arena technology allowing for expanded 

data collection, he said. Since then, Orlando’s data and analytics division has grown to 15 people from three.

At the moment, “we are super-focused on personalization and using the data we have to inform our interactions with you,” Riola said. “Not only the basics — what games did you come to, where did you sit, what did you spend? But now I think a lot more where we’re predicting how likely you may be to convert to a season-ticket plan.”

The Magic and other teams are becoming more predictive in their analysis because they have more detailed information, particularly with the shift to mobile apps that encourage fans for most or all of their transactions: digital ticketing, ordering food and drink, buying souvenirs, following the game with statistics and other information. More teams are pushing fans to their apps by providing discounts and other offers, spurring sales while creating an easy-to-gather history of buying habits. 

Detailed real-time information helps teams and venues adapt to preferences and buying patterns. It also allows them to segment and target various types of fans while adjusting to snags as well as demand surges, or lapses, for parking and scanning tickets outside the venue to buying concessions and merchandise inside. And the more that is known about who’s watching and buying, the more that can be shared to retain a corporate partnership or land a new one.

“The more analytical storytelling we can tell our partners [the better],” said Elgin, the Hawks executive. “Our fans are this age, our fans shop here, our fans behave this way, our fans are going to transfer their loyalties because we’ve got studies showing the incremental growth a partner might get with survey data and being able to tell a complete and clear picture.”

Team executives leading data and analytics departments and strategy across the board said that while they and their bosses emphasize maximizing revenue, it’s not the only factor considered when setting strategy.

Further, they said judging return on investment from data teams, research, software and other support isn’t a one-to-one proposition. In other words, teams aren’t saying they’ve spent $2 million in a year on data and analytics so therefore programs need to generate $4 million.

■  ■  ■  ■

Over and over, executives said collecting, synthesizing and analyzing data to better serve fans and sponsors is simply the way business is done — everywhere.

“Larry Lucchino, our former CEO, used to say that which can be measured can be improved,” said Tim Zue, executive vice president and chief financial officer of the Boston Red Sox.

Zue said ushering in data-driven decision-making made the Red Sox take what now seem like obvious steps — steps that make financial sense. Case in point: Until 2013, all tickets were priced the same, whether for Opening Day, a nondescript weeknight game in April or for a pennant-stretch matchup in September against the Yankees.

Like many teams, the Red Sox find themselves tinkering with and monitoring ticket prices and secondary prices to get a better sense of what they should be charging. Tiered and dynamic pricing have become commonplace in sports, though with considerable variations. But Zue’s point is that what now seems like a foregone conclusion barely existed just six years ago.

Red Sox EVP and CFO Tim Zue said data has driven decisions, such as dynamic pricing, that seem obvious in hindsight but were revolutionary six years ago.
Photo: Billie Weiss / Boston Red Sox

Zue said the Red Sox and other teams have moved more marketing pitches online because they can be better monitored.

“You can say, ‘I spent $100,000, this was the click-through rate, these are the people that purchased all the way through,’” he said. “This isn’t unique to us, all the teams are doing it: ‘Here’s how many tickets I sold …’ It’s easier to justify spends like that when you can tell my boss, [Red Sox President] Sam Kennedy, ‘Yeah, we spent $100,000 but we sold $1 million worth of tickets.’”

Such examples stand out and are highlighted, but Zue, like other executives interviewed for this story, stressed organization-wide commitments to use data for a range of decisions, some of which can be quantified in the near-term and others aimed at long-range objectives.

“It’s more of a return on objectives than it is a return on investment,” said Matt Kobe, who is the Chicago Bulls’ vice president of business strategy and analytics.

An example of not-just-revenue strategy: Data analysis told the Bulls their ticket mix all but excluded students and families. Soon after, the team introduced ticket prices targeting students and families and saw increases in attendance among both groups.

Getting buy-in from fans, and keeping it, are trickier than ever for brands of all types.

Consider the spam-weary consumers who are often just as benumbed from tone-deaf marketing messages sent by companies and brands they actually like and follow.

The latter could entail a box-seat buyer bombarded with offers for discounted grandstand tickets (an unlikely pitch that should have been ferreted out through buying history data) or a far-flung fan who follows her favorite team from 2,000 miles away on TV and social media only to receive constant entreaties from that team to buy season tickets.

VenueNext CEO Anthony Perez sees room for teams to take a second look at conventional wisdom established by the initial wave of data and analytics findings in sports business.

Perez, who played a key role in the Magic’s analytics push before leaving last year, said demand for additional data sometimes overwhelms more effective approaches for teams. Case in point: Teams and venues will often push for required log-in accounts to obtain names and email addresses to bolster databases. That’s not always a good idea because many people will simply dismiss the app or page altogether.

“You have to be really careful when you force that on someone,” Perez said. “Let’s slow-play it a little bit, let’s show them the value. Then start asking for information or think how far you can get without that information.” 

Erik Spanberg writes for the Charlotte Business Journal, an affiliated publication.