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Articles August 19, 2024

Create Lifelong Fans and Drive New Revenue with AI-Optimized Journeys

Arjun Baradwaj Jon Bradway Roberto Castro
Authors
Arjun Baradwaj, Jon Bradway, Roberto Castro

Our recent article, “The Power of Fan Data: Using Fan Data to Win the Engagement Game,” focused on why organizations should develop and activate a data strategy, which culminates with owning your data and unifying customer views. Once you have these critical pieces in place, you’re ready to take the next step in your data evolution.

In our second article in our fan data series, we’ll focus on how you can meet fans where they are with personalized fan journeys. Meticulously crafted journeys alone are a powerful tool — but when combined with a managed AI model, these journeys can be effectively optimized and scaled to account for the tremendous volume of fan data available.

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With Data-Driven Fan Journeys, the Possibilities Are Endless

Fan journeys run the gamut, which starts with the obvious variance from sport to sport. For example, attending a golf tournament is a vastly different experience than attending an NFL game. Before you even step foot on a course or into a stadium, how a fan purchases a ticket, travels to the event, and engages with each respective sport would be unique. But the differences between sports is just the starting point.

In the examples above, this only factors in a fan who is attending an event. What about the fans tuning in from home? Or a traveling fan who might visit from out of state to watch their favorite team? Even accounting for all the possibilities, organizations also need to look beyond the season itself: a true year-round fan journey would factor in how fans engage during the offseason, too. 

Consider the NFL, and the offseason milestones and events they’ve cultivated: the league markets the draft, free agency, schedule announcements, and more to create year-round engagement. And in every possible scenario, there’s the potential to connect with fans.

Connecting All the Potential Touchpoints, Context, and Interactions

To create detailed fan journeys, organizations must understand all the in-season and offseason possibilities touched on above — it takes a command of all of the potential fan journey touchpoints, and only then can you map them to specific data points. This helps you identify the appropriate context and determine the right technologies and channels to create a cohesive engagement strategy. 

To illustrate these connections, let’s shift to baseball and a specific scenario; we’ll use what we refer to as “the first inning problem.” Often, you’ll notice a stadium is empty in that first inning, which isn’t ideal for the fan or the organization. By leveraging existing team or MLB channels, you can uncover data points and deliver timely, personalized offers that might help you address the first inning problem:

Comprehensive Traffic Data

With comprehensive traffic data, you could inform fans of faster travel routes or offer deals with transportation partners (e.g., Uber or Lyft).

Geolocation Data

Using geolocation data, organizations could promote their own on-site parking options, which expedites entry, or send concession deals to tempt fans to come earlier instead of tailgating or “pre-gaming” at a local watering hole.

Partner Data

Similarly, you could use partner data to create co-branded events that feature food or merchandise discounts to entice fans to arrive at the stadium earlier.

General Entry Guidance

Teams could also send general entry guidance — for example, if lines are shorter at a specific entry point — along with a concession deal to help fans arrive for the first pitch.

These examples have one critical, common thread: they put the fan first. Because by addressing their problems, you can solve yours.

Only AI Can Game Out All the Fan Journey Possibilities

As noted in the examples above, solving for the fan first means thinking beyond standard martech efforts. When broad push notifications are sent out to fans without any personalization or segmentation, they do not resonate or inspire action. But creating detailed fan journeys, then connecting them with all the data available to you, is a tall, complicated task. Uncovering all the possibilities, possibilities that address fans’ needs while driving revenue, would take a human — even a team of workers — countless hours.

This is where AI serves as a problem-solving accelerator. By streamlining the data-gathering from all available vendor, partner, and internal channels, and loading that data into a managed AI model, you can expedite analysis of information and optimize the fan journey. The model will not only uncover potential gaps — it can identify additional challenges that can be turned into opportunities.

In talking to our clients, we often hear that they know they need to optimize their fan journeys — they just struggle to find consensus on which ones to prioritize. But with AI, you don’t have to choose. You can optimize them all. 

Initially, a managed AI model reduces the time and cost to reach the valuable insights that will inform fan journeys, allowing organizations to scale accordingly. There’s a definitive and positive domino effect:

Repeatability allows you to test and learn more rapidly, which in turn allows you to react quickly to changes in an ever-crowded sports and entertainment landscape.

AI-Optimized Journeys Lead to Hyper-Personalized Fan Experiences

From the “Big Four” leagues to up and coming niche sports, highly detailed fan journeys present an incredible opportunity to sports organizations. The advances in AI can streamline the myriad ways you can deliver value for fans and sponsors that aligns with your desired business outcomes. Rights holders who possess a true golden record are perfectly positioned to leverage an AI model that can extrapolate the infinite possibilities to deliver repeat experiences that drive fan loyalty. 

AI is at its best when it quickly and cost-effectively hits the sweet spot of solving those business problems, all while meeting your fans exactly where they are, providing them with personalized experiences that will engage them during the season and after, within your arena or in the comforts of their own home. With a managed AI model turbocharging your efforts, soon your biggest challenge will simply be deciding which fan journey to optimize next.

This article is part two of our comprehensive series delving into the transformative power of fan data. Read part one here. Stay tuned for more insights and actionable strategies to harness the full potential of your fan data and become an industry leader in data-driven innovation.

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Arjun Baradwaj

Arjun Baradwaj

Managing Director, Data & Analytics

Arjun is a Data & Analytics practice area leader at CapTech, focusing on data strategy and productization. Arjun has worked with several data clients across industries, with extensive experience in the sports space.

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Jon Bradway

Jon Bradway

Principal, Sports, Media & Entertainment Lead

As lead of CapTech's sports practice, Jon partners with leagues, media companies, and technology firms to create the next generation of competition and fan experience.

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Roberto Castro

Managing Director, Business Development

Roberto is responsible for expanding CapTech’s golf and sports practice by connecting sports organizations with technology solutions. Roberto previously spent 9 seasons on the PGA Tour and played collegiately at Georgia Tech.

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