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NFL's Raiders use analytics to engage new customer base

The franchise's move to Las Vegas forced it to modernize its analytics stack as it engaged a new fan base and cultivated the unique opportunities present in Sin City.

When the National Football League's Raiders moved from Oakland to Las Vegas before the 2020 season, they needed analytics to understand a new -- and unique to football -- customer base.

Their existing analytics stack, however, was insufficient.

To address the team's needs, and to ultimately engineer a modern analytics stack designed to learn about their unique customer base, the Raiders employed Data Clymer, a San Francisco-based consulting firm with experience building data platforms for sports franchises.

In addition to the Raiders -- and Macy's and Petco, among others -- clients include baseball's San Francisco Giants and NASCAR.

The system the Raiders were on before wasn't going to cut it.
Aron ClymerFounder and CEO, Data Clymer

"The system the Raiders were on before wasn't going to cut it," said Aron Clymer, founder and CEO of Data Clymer, during a session at AWS re:Invent, the hybrid virtual and in-person conference hosted by the tech giant.

After scrapping the Raiders' previous analytics stack, Data Clymer helped the team build a stack that includes:

Unique circumstances

The Raiders faced two significant challenges in learning about their customers and subsequently figuring out how to engage them.

The first was that they were new to Las Vegas. No one in the city was loyal to the team the way fans were loyal to the Raiders when they were in Oakland.

The Raiders, who were original members of the American Football League before it merged with the NFL, began in Oakland in 1960 and remained there through 1981. From 1982 through 1994, they played in Los Angeles. And after returning to Oakland in 1995, they stayed there through the 2019 season.

If they had any fans in Las Vegas, it was from afar. So without a longstanding local fan base, the Raiders needed to find ways to engage potential customers in their new home city.

Compounding the problem -- the second challenge -- is the identity of Las Vegas itself.

The city's population is about 650,000, and the metropolitan area's population is about 2.25 million. Among NFL teams, the Raiders' new home region ranks 22nd, slightly behind Pittsburgh and just ahead of Cincinnati and Kansas City.

But Las Vegas is a more popular tourist destination than all but five other American cities.

The massive influx of people attending conventions and vacationing in Las Vegas represents a huge marketing opportunity for the Raiders.

Another difference -- and opportunity -- is the Raiders' ownership of their own stadium. The Raiders were tenants at the Oakland Alameda Coliseum. They shared any revenue made from concession sales during home games, and they saw none of the money from concerts and other events held at the Coliseum.

Now, the Raiders have the potential to host concerts and other events in Allegiant Stadium -- by far the largest venue in Las Vegas -- and reap the benefits.

"I think they might make more money off of events than football in Vegas," Clymer said. "Las Vegas has never had a venue this size, so there are a lot of performers and acts that can come to Vegas who couldn't come to Vegas before. There's a whole new opportunity for the Raiders with their data."

To market to a new fan base, engage an additional customer base of visitors and develop strategies for maximizing Allegiant Stadium, the Raiders needed analytics.

The problem

As the Raiders were making their transition to Las Vegas and attempting to understand an entirely new customer base with vastly different characteristics than the one they left in the Bay Area, their analytics stack was not nearly fast enough.

The technology they used in Oakland was antiquated. It sufficed when the franchise knew and understood its customer base, but when the team was essentially starting over and seeking new opportunities, it needed a modern analytics stack capable of leading to insights in hours and days rather than weeks and months.

According to Clymer, the Raiders were using a third-party managed services system while in Oakland.

"This is typical of a lot of sports teams," Clymer said. "Five or 10 years ago, [managed services] was a great idea. Outsourcing made a lot of sense. But data has gotten a lot more complex and the analytics they need to do has gotten more complex, so these systems aren't flexible enough for them. On top of that, there's a lot of latency and slowness getting the job done that they need done."

Because of its antiquated analytics stack, data was siloed, query speeds were slow, it was unable to handle complex data projects and flexibility was lacking, according to Clymer.

In addition, the organization's analytics workflow was a relic. Even the smallest changes required the submission of a ticket to a centralized IT team, and the turnaround time was weeks to months.

It was a problem many other organizations -- not just those in the realm of sports -- faced, and many that haven't yet digitally transformed continue to face.

"Things were slow, and there was significant downtime," Clymer said. "All of it built up over time and created a lot of friction for the team. It's not unique to the Raiders -- I've heard this story many times across not only major league sports teams but in industry in general."

The Raiders needed to modernize their analytics to both cultivate a new customer base and maximize opportunities at hand.

The solution

With speed and performance at a premium for the Raiders as they attempt to understand a new customer base and maximize new opportunities, a cloud-based analytics stack was a must.

Also critical was eliminating data silos and migrating all their data to one place.

With customer data coming in from sources including Ticketmaster, the NFL itself, applications such as Salesforce, and other sources like stadium concession sales, the team decided to use Matillion for its ETL needs.

Matillion, a partner of Clymer, is an ETL platform the firm often builds into the analytics stacks of its clients, including the Giants and other sports franchises.

Matillion enables the Raiders to extract data from those multiple transaction sources and funnel it into a single environment, blend Python and SQL to create usable data sets, and then push those data sets out to where they can be accessed and viewed for analysis. That could be back into applications such as Salesforce, cloud data warehouses for storage or up to BI tools for analysis.

In the Raiders' case, that's Snowflake for storage and Tableau for analysis.

In addition to Matillion, the Raiders also use Melissa Data during the ETL phase.

The platform helps eliminate data duplication such as creating multiple accounts for a single customer who may have bought tickets through Ticketmaster and a jersey through the NFL's website, and better enables the Raiders to gain a better view of each customer.

"We end up getting a golden record of a fan in the data warehouse," Clymer said, referring to the concept of a single master set of fully trustworthy data.

"The benefits for the Raiders are all about control. They now have a fully customizable solution, it's team-owned and not third-party hosted, the data is all centralized and there's deduplication of fan data," Clymer continued. "They have a better record of the fan, and … the ultimate goal is to understand their fan base better and take action on that."

But while the Raiders' analytics stack may now be in place, the franchise is just getting started with its efforts to engage a new customer base, Clymer continued.

The team is able to rapidly analyze data, and develop more targeted marketing campaigns and new approaches to merchandise sales and fan engagement. It's also finding new customers, and preparing to host events beyond football.

But so far it's developed only three data sets. It will develop many more over time as the Raiders use analytics to determine how to cultivate a new customer base and find growth opportunities.

"It will never end," Clymer said. "These data projects go on and on because you're always coming up with new objectives for your business, you always have new challenges, and there's always new data you can apply to get answers and take action."

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