When we first began working with pro sports teams, I attended a trade show session hosted by a highly regarded sports data guru. During his speech he enthusiastically promoted a technical product set that offered a data-driven approach to understanding the “fan experience.”
To demonstrate the power of his product, he described a scenario that required the quick and immediate production of a complicated report:
“Let’s say I wanted to run a report that included: All female single- game buyers,” he began, holding his index finger in the air as he casually paced the stage. “With a college degree,” he continued, extending a second finger. “Who also attended 2 or more home games in the last 3 years,” followed by a dramatic pause, “and also have kids still at home,” two more fingers now pointing to the ceiling. “Finally, let’s say that the list we need also requires us to know which of these people also purchased ice cream or candy in the venue,” the thumb serving as an exclamation point, ensuring that everyone in the room grasped the degree of difficulty involved.
He strode the width of the stage in dramatic silence, his arm and five fingers held high until he arrived back at the podium where he clicked the mouse a few times, and enthusiastically declared:
“Bammo! Look how easy that was.”
The audience was impressed; audible oohs and aaahs floated above the din of glasses being clinked and elbows being rubbed in the atrium bar immediately outside the meeting room. Years later, I can admit to being momentarily captivated by the relative ease at which the guru quickly and easily parsed a large dataset to arrive at his “bammo” moment.
My captivation, however, was quickly replaced by honest confusion: Why would someone ever need this report?
After the presentation, while most of the room was hustling to add a few more decibels to the volume in the bar, the speaker was gracious enough to humor my question while he packed his materials. Maybe he was still basking in the warmth of the ovation he had just received. Or maybe, he sensed that I was new to sports and he genuinely wanted to educate a novice who was clearly in over his head. Whatever the reason, the next three minutes solidified my resolve to go “all-in” on sports.
“You see, Joe,” the education began with my guru clearly too focused on answering my question to peek at the name on my business card which was still face-up in front of him. “It’s all about targeting. These teams have to be smart about how they sell and market.”
Now he was speaking a language I understood. A sensible answer must be right around the corner!
“And you see, if you understand who the fan is, you can craft relevant messages,” he continued, enthusiastically sharing thoughts that I understood and wholeheartedly agreed with.
Still, I wasn’t able to fully connect the example he showed – moms who purchased various combinations of ticketing products and sugary concessions – with my understanding of the revenue goals of most teams. So, I pressed the speaker to help me better understand.
“So why did you use these specific examples? Have you identified a correlation between this combination of fields and outcomes of future sales and marketing efforts? Otherwise stated, have teams found success in targeting these types of people with similar demographic and behavioral attributes?”
“Oh that’s not what we do. We encourage teams to collect as much data on the fan as they can get their hands on. We store and organize the data in such a way that allows them to access it in order to build the campaigns they want. That’s what you saw today. These teams need to be nimble so that they can effectively target market to people with unique attributes.”
Accepting that the example showed earlier in the day was just an example of what his approach to data management could accomplish, I wanted to better understand the industry mindset:
“But if they’re storing lots of data that doesn’t correlate with revenue outcomes or even necessarily align with specific business goals, doesn’t that just create a lot of additional overhead and confusion.”
Sensing that my sincere questions were suggestive of something other than a sports newbie simply trying to better understand industry trends, the presenter began to take a defensive posture.
“You have to understand, John (still not my name, but ‘A’ for effort), big data is a whole new world. None of us really know how we are going to use data in the future. That’s why it’s important for these teams to hold on to everything.”
Huh? Did this guy just attempt to convince me that it’s rational for organizations to pay to acquire data whose value was undefined – and then pay a lot more for an expensive infrastructure to ingest it, organize it and store it because it might be worth something one day? Is digital hoarding a thing?
Something about my reaction alerted him to the deafening alarm blaring from my internal B.S. detector. In that moment, the charming data guru’s generosity abruptly halted.
“I have people waiting on me, and I am going to owe all of them a drink if I don’t get out there. But it was fun chatting, Josh (strike three). Let’s stay in touch.”
Flash forward to the present. Many teams are now realizing the inefficiencies that result when they approach data acquisition, storage and usage like a squirrel approaches nut acquisition and storage – hoarding and hiding nuts in places they will never find and likely never need or miss.
Without a strategic plan for using the data to support sales and marketing goals, teams waste significant energy and expense on ‘as much data as possible’ and ‘hunches’ rather than focusing on building a reliable data set that is required to achieve clearly articulated business goals. The first step in building a strategic plan must pinpoint the specific drivers of success and failure related to each goal rather than arbitrarily creating relationships with the data. The result cancels out the noise, expense and inefficiencies that comes with excess data.
A decade-long economic boom shielded most teams from the need to deeply evaluate business priorities. The global catastrophe created by the COVID-19 virus and the subsequent impact on budgets and personnel, demands that teams examine their strategies and implement processes that effectively do more with less. Any “comeback” strategy requires teams to use data in a way that creates efficiencies for every member of the sales and marketing team. Without the safety net that yesterday’s abundant resources provided, teams have to be rapidly outfitted with smart tools that prepare them to thrive in the new world. These toolkits need to be built upon a solid foundation of meaningful data that power meaningful business results. Nicely packaged lists of college educated moms of sugar addicted kids with no relevance to business priorities are a thing of the past.
- DATA STRATEGY OR DATA HOARDING? - September 28, 2020
- Four Questions that will Kill Sports Comeback Strategies - August 25, 2020
- Larger Prospect Pools = Greater Sales?
Part 5 of the piLYTIX Sports series “Challenging Conventional Wisdom”- September 12, 2019