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Big Data, Beer, and Influencing Rogers

Since his arrival, Mark Shapiro has been pushing the Jays forward on multiple fronts. His baseball decisions have been much debated, but we know there has been a heavy investment in building analytical capability in the baseball operations department. Arden Zwelling wrote a great piece about Toronto’s new, highly publicized high performance department, but the Jays are also trying to catch up to other teams in the other baseball big data revolution: Marketing.

To wit: The hottest job in Toronto lately might have been the newly created Vice-President, Strategy & Business Analytics for the Toronto Blue Jays (rumour has it that several hundred qualified candidates applied for it). Whoever gets the job will report to Andrew Miller (no, not that Andrew Miller), the Executive Vice President, Business Operations for the Jays. Miller’s last role? Vice-President, Strategy & Business Analytics for Cleveland.

In the last few years many baseball teams have significantly invested in their business departments to identify ways to sell their fans more things, more often, and for higher prices. As you might expect, Cleveland was one of the leaders, and Miller is looking to build that capability in Toronto.

So, why should we, the Toronto Blue Jays fans, care about this? For one, it probably means that in slow, steady and subtle ways, your fan experience is going to get both better and more expensive. But more importantly, because Rogers is who Rogers is, if they can get it right, it might mean a consistently better team.

The introduction of dynamic ticket pricing has likely been the most high-profile change to business practices. Some people see this as Rogers being greedy, but it’s easy to look at it differently. We already had dynamic pricing, and it was called Stubhub. If people are willing to pay more for some games, isn’t it better for that revenue to go to the club, rather than a middleman? The richer the team is, the more likely they are to spend money on players.

The ticket pricing is obviously the big splash, but there will also be many lower-profile changes that will affect the fan experience. In 2013, Ben Lindbergh wrote an article about a baseball business analytics presentation he attended and it featured Cleveland.  They were using data to understand the most successful promotional giveaways (cap days, apparently – expect more of those) and the best days on which to have them; they were learning about when and how to promote games to their fans. Their more complete understanding of their fan base even drove them to create a Kids Clubhouse.

As fans, these are good things. If they learned cap days bring out the crowds, that means we probably like caps and will be happier when we get one. If they advertise tickets to us when we’re most likely to buy, it means we probably wanted to go to the game and going will make us happy. They will get better at predicting crowd sizes, and therefore better at staffing for them (a constant irritation at the Dome).

Data analysis will make them better at knowing what merchandise we want, and at predicting the sizes they will need. So, I will be less likely to find empty shelves when I shop for my 4 and 2-year old girls. That will make me really happy, and I’ll spend more.

There’s a next level to this, though. As the team collects more data, they’re getting more sophisticated. They’re
building profiles of different fans – the sections they like, the food they eat, where they watch the game when they’re not there, and which players they follow on social media. Partnerships with major data companies will help them analyze it all. Soon, advances in artificial intelligence will allow the team to create “robot” versions of these fans and let them interact with each other in computer simulations. These interactions will then predict the right way to serve each fan type and how much those fans are willing to pay. They will continue to get better at creating the perfect experience to separate team followers from as many dollars as possible.

To use an example, I really like craft beer.[1] I also like sitting in the 100 level of the outfield. So the robot fan version of me will interact with all the other robot fans, and collectively they will predict where most of the fans who like craft beer are likely to sit. Once the club has accomplished this, they can locate a craft beer stand near that section and then start to promote it: if you like craft beer, try sitting in this certain section that they know you are likely to choose anyway. And they’ll communicate these promotions directly to me since they will know what fan type I am. My baseball experience becomes a baseball and craft beer experience and again, I’m both spending more and I’m happier. And likely drunker.[2] The team wins, and I win.

So, the goal of all these things is to increase the value of each individual fan of the team, right up to their maximum willingness to pay for any product or service and the maximum value of their attention for sponsors. This is not a new goal, but analytics makes achieving it a lot easier.

This is where it gets really interesting: Toronto is one of only two corporate-owned MLB teams (Atlanta is the other). This is a gross simplification, but that makes them more likely to be thought of as a “business unit” than other teams owned by a billionaire passionate baseball fan like the late Mike Illich. Through a purely “investment-return” lens, the player budget is justified by the number of fans it is likely to produce, as fans are the basis for every element of revenue, from advertising to ticket sales to bat-shaped pens.

But what if you could make each fan worth more? If you could increase your revenue by 10% with no increase in attendance simply by understanding the people better and giving them what they want, when they want it? A billionaire fan-owner probably thinks this is great but I doubt it changes their willingness to spend. But for Rogers? If you told them you could increase the average cable subscriber revenue by 10%, they would absolutely pour more money into acquiring more cable subscribers. In sports, winning drives fan acquisition more than anything, and all other things being equal, a higher payroll increases the chance of winning. So, if you can actually increase the value of a fan, the case for investing in winning becomes much better.[3]  

It’s easy to see the investments in high-performance and data analytics through the same lens: it’s Mark Shapiro aiming to increase the return on investment of each payroll dollar, giving him a better case to push for a higher budget with a data-driven corporate owner.

I don’t know about you, but I’m getting used to this team winning, and I don’t want it to end. So, bring on dynamic pricing. Bring on craft beer at higher prices and more hat promotions.

Come and get me, robots. Let’s do this.

Lead Photo: © Tom Szczerbowski-USA TODAY Sports

FOOTNOTES
[1]:Or at least I think I do. In a blind taste test I probably couldn’t tell an IPA from a Labatt 50.

[2]But wait – what about the fan who can’t afford all this?  The one who gets priced out by dynamic pricing and the elimination of things like the Ballpark Pass? If we’re being charged more because we’re willing to pay, how does the team nurture the next generation of fans? Do they alienate fans who love the team, want to participate, and now can’t afford it? This is its own article, and worth a real discussion. More to come on this, as it should be possible to do both.

[3]The same argument probably applies to small-market teams, but that makes the article less punchy so let’s not digress…

 

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3 comments on “Big Data, Beer, and Influencing Rogers”

Arjonn

As a former marketing exec, I’m very familiar with the concept of aiming to increase the average customer spend, and also of understanding that part of this is catering to particular segments of the total audience rather than treating everyone as if they were the same all the time. That said, understanding why I’m being charged more, for example, to attend a weekend games vs. a weekday one against the same opponent doesn’t mean the fan side of me has to like it, especially since I don’t believe that increasing the average spend will slow the rate at which prices will continue to rise, at least not until they reach a point where meaningful numbers of fans buy less and/or stop buying altogether.

Ryan

great read. business side of analytics rules – keep it up this is really interesting. hope to read more from you in the future

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