Modern Cloud Analytics Creates Winning Customer Experiences

The Utah Jazz create winning customer experiences with modern cloud analytics.

Putting on a winning performance is just one factor in creating memorable fan experiences. For championship teams, it’s rare for one factor to be the reason for success. Success breeds success. For Utah Jazz fans, compelling customer experiences begin the moment you arrive at the Vivint Smart Home Arena parking lot located in Salt Lake City, Utah. They go well beyond. They span how you interact while attending the game and even continue until you exit the arena. Why? Because Larry H. Miller Sports & Entertainment, the owner of the Utah Jazz and Vivint Arena, realize that creating memorable customer experiences builds customer loyalty. And customer loyalty brings this NBA team’s fans back to their seats to cheer on more winning games.

41 regular season home games per year (in a non-COVID-19 year) to maximize customer experiences.

Considering the average basketball game is three hours, with fans arriving one hour before tip-off and departing upwards of one-hour after the final buzzer, Larry H. Miller Sports & Entertainment has the opportunity to delight and surprise their customers using data analytics for 5 hours! Modern cloud analytics, using machine learning and artificial intelligence on a flexible platform, means they can scale analytical workloads to match the pace of their business.

Dustin Spangler Vice President of Data and Analytics

Dustin Spangler Vice President, Data and Analytics

Mr. Spangler, vice president of data and analytics for Larry H. Miller Sports & Entertainment, has more than 20 years of experience in helping companies drive value from their business intelligence and analytics objectives.

Larry H. Miller Sports & Entertainment (LHM) sees customer experience as a way to improve customer satisfaction, create loyalty, and increase customer per capita spend.

Their customer experience begins before you even arrive to the arena. Using Teradata for modern cloud analytics, like machine learning and artificial intelligence, LHM uses fan attributes to classify, cluster, and autonomously optimize customer segmentations for targeted and relevant customer experiences and promotions.

“There’s a number of things that we’re doing to try to help improve fan experience but as a business we’re trying to increase the per cap or the dollars that they spend at the arena. And, so sometimes that means a timely promotion that is pushed to a persona that we believe would react to that promotion.”

Dustin Spangler, Vice President, Data and Analytics
Larry H. Miller Sports & Entertainment

Over 80 data sources are integrated including social media, digital, CRM, telco, ticketing, WIFI, beacon, and camera data.

Combining internal and external data sources onto a single cloud analytics platform is the basis for creating a full picture of who customers are and what they want to experience.

Data Integration: Creating A Complete Customer Picture for Experiences Fans Want

It all starts with integrating owned and third-party data via their partnership with Ticketmaster Entertainment, Inc., a ticket sales and distribution company.

Using the Utah Jazz mobile app, your ticketing data is loaded to the app and begins to serve the basis of who you are as a fan. LHM uses this information to understand whether you’re a “fair weather sports fan” who attends a couple of home games, a season ticketholder attending every game, or a casual fan attending a handful of games and purchasing tickets on the secondary market. The basis of this begins to cluster customers based on context and behaviors.

Those that bought season tickets and were loyal fans who come to almost every game or shared the tickets with friends or family. And then there are those that buy a lot of season tickets that go into a secondary, and potentially even a third, market. We look to see the actual end-consumer that came to the game, what they actually paid, and what their overall experience was. We want to cut out a little bit of the middleman and we’ve strategically raised prices for those that were buying to resell while holding true on lower prices for those customers who are true and loyal fans.”

LHM then uses its mobile app to push relevant and timely offers based on your fan profile as you make your way through concessions like the team store and food and beverage concessions within the arena!

With every customer interaction and transaction, LHM creates a more complete picture of their customer segments and behaviors. Artificial Intelligence performs customer segmentation based on unique and common attributes constructed from predefined and learned patterns built with internal and external data sources. Machine learning refines segments and customer classifications. While pathing analysis integrates multiple customer interactions to identify friction points that may lead to customer attrition, specifically for season-ticket holders.

Teradata Vantage on AWS for Modern Cloud Analytics

LHM’s highly varied and cyclical environment creates a burst of analytical workloads driven by customer interactions in a short five-hour window from fan arrival, to tip-off, to final buzzer, and the last fan’s arena departure. Their desire for a modern cloud analytics platform, capable of the flexibility and elasticity to rapidly scale up and down, led them to Teradata Vantage on AWS.

“The cloud provides us greater flexibility. In terms of changes in the market, to be able to have excess capacity at our availability and to be able to interact across multiple applications and multiple services in the cloud, makes that a lot more seamless and easier for us to implement.”

Their analytical journey has accelerated rapidly with the help of Teradata.

Teradata Data Labs gives users the power and freedom to explore and examine combinations of new and existing data that can pinpoint new trends, uncover insights, and address pressing business issues. Whether it’s an approach of ‘what happened’ (descriptive analytics), to ‘what is happening’ (prescriptive analytics), and ‘what could happen’ (predictive analytics), LHM requires modern cloud analytics capable of the machine learning and AI business analysts and data scientists need, at scale.

“Everybody wants to move towards artificial intelligence and machine learning to be able to understand and see patterns that aren’t naturally apparent to the human eye. Leveraging Vantage to do our machine learning and our AI speeds up that process from what we can get from ideation all the way through to insights and to creating answers.”

“We strive to not just collect data, but to be able to add insights and push actions back through the application or other services.

That’s where we’re going to see that scale up. We may need that for a three-hour period and then it goes away for the next day. The exciting thing about consumption pricing is we still have all of the great features of Teradata workload management. However, when there is a need to scale up and move above the cost controls and the system management, it’s simple and easy to auto-scale up and be able to respond as we should.”

Teradata Vantage on AWS with consumption pricing creates a winning combination to match the winning culture of the Utah Jazz and Larry H. Miller Sports & Entertainment.

Looking ahead, machine learning and AI present amazing opportunities. As Larry H. Miller increases their advanced analytics, they find new ways to treat data as an asset and rapidly add insights to decisions to keep the Utah Jazz at the top of the standings and create championship-caliber customer experiences.

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Larry H. Miller (Utah Jazz)