AI Insights, Spending Data Needed to Truly Unlock Fan Loyalty

AI Insights, Spending Data Needed to Truly Unlock Fan Loyalty

Building loyalty isn’t about apps, points, or rewards—it’s about understanding fan behavior on a deeper level and using those insights to create meaningful experiences. The strongest loyalty programs don’t just reward engagement; they harness data to predict behaviors, personalize communication and offerings, and unlock sustainable, long-term revenue growth for the organization.

Sports loyalty has evolved in recent years from gameday points programs into integrated ecosystems that spur ticket and merchandise sales, enhance sponsorship activations, and strengthen the club’s position amongst media rights holders. Some of the more progressive programs include:

• NBA ID
  The global program integrates data from NBA League Pass, fantasy games, and digital content. Powered by Microsoft’s AI, the league claims implementation has resulted in a 40% jump in app downloads, a 50% increase in League Pass subscriptions and a 48% lift in League Pass viewership.
  

• The Collaboration Between Salesforce and McLaren F1
  McLaren F1 has consolidated all of its data from TV, digital, and live events using Salesforce's Data Cloud and created 360° fan profiles that drive (pun intended) real-time personalization. According to Salesforce partner Kofana, the initiative has boosted fan satisfaction ratings from 70% in 2018 to 88% in H2 2022.
  

• The Collaboration Between Fanatics and the Indianapolis Colts
  The Indianapolis Colts partnered with Fanatics to integrate the sports retailer’s virtual currency into its fan app. Season ticket holders now earn ‘FanCash’ that can be redeemed for various benefits, including merchandise online and concessions at the stadium (if converted into credits on Colts Connect).

The cross-platform integration is getting closer to promised land. The next step in loyalty’s evolution is for programs to become POS, payment, and card linked.

That will enable sports properties to derive actionable high-value insights, and meaningful incremental revenues, from everyday spending. As fandom increasingly takes place outside of the stadium (think: at home, online), having a firm understanding of the fans’ behavior(s) becomes more and more important.

“True fan loyalty is built on the fan experience, preferences, and emotional connections [to the organization] across every measured touchpoint,” Vincent Sarafa, who has launched fan experience and loyalty programs across the NFL, NHL, NBA, and Fanatics, among others, said. “By integrating AI-driven insights with real-world spending data, properties can create hyper-personalized fan experiences that drive deeper engagement and unlock [lucrative] new [income] streams.”

Payment-linking technology adds a powerful layer to loyalty programs by tying everyday expenditures to team rewards. The process creates an ‘always-on’ relationship between the fan and organization that ultimately drives higher lifetime values and stronger brand attachment.

That’s because if every transaction those fans make —from ticket and concessions to digital purchases— can be captured in real time, teams would have a true view of fan spending patterns. And those granular insights could be used to fuel engagement and incremental spending.

Organizations with access to this data can construct interactive dashboards, using platforms like Oracle CrowdTwist or FanThreeSixty, to segment their fans based on demographics, spending habits, and engagement levels.

Knowing who the top 20% of spenders are would be helpful to an organization trying to make contracted sponsorship activations more efficient (think: it could introduce VIP perks where partners offer exclusive, real-time, personalized rewards). Detailed attribution models can now tie these promotions directly to incremental sales, providing corporate sponsors with the verifiable ROI that justifies premium activation fees.

A rights owner could also isolate the most digitally engaged fans and deploy messaging to them that mirrors their actual spending behavior. This refined approach has proven to drive higher conversion rates.

Or it could identify high-value fans that may be likely to upgrade to partial or full-season ticketing plans and push out hyper-targeted offers that spur top line growth.

Integrating transaction data along with engagement metrics can strengthen a rights owner’s negotiating position with broadcasters who value the additional context too.

Predictive models developed on AI-powered platforms, like Elevate’s EPIC, combine loyalty interactions, app engagement, and live viewership data to identify ‘engagement spikes’ during a game broadcast. Organizations leveraging those insights have been able to secure media rights deals 10–15% higher than those going to market solely with traditional ratings.

Leading loyalty providers, including Cardlytics, Rakuten, and Visa/Amex Offers, all capture and return detailed spending data (think: merchant, location, amount, and time) and fan behavioral metrics (think: viewers, activations, redemptions) to club partners.

The meaningful top line opportunity underscores the need for rights owners –particularly those with large, engaged fan bases– to move beyond traditional loyalty models and embrace a modern, data-first approach.

A club’s fan base needs to be sizable for it to collect enough data to influence future media rights negotiations. Organizations without critical mass may also find the payment-linked strategy to be cost-prohibitive.

Turnkey SaaS solutions, like Oracle CrowdTwist, FanMaker, and Socios.com, offer comprehensive loyalty ecosystems on a subscription basis. Prices range from the low-to-mid six figures (think: single-team implementation) into the low seven figures (think: league-wide rollout).

While off-the-shelf SaaS platforms can deliver rapid deployment and proven performance, they’re built for the masses and lack the bespoke features that can set a business apart. Custom-built solutions —developed on API-first frameworks with advanced machine learning libraries, like TensorFlow or PyTorch— offer superior data control, tailored analytics, and unique intellectual property.

The initial investment to do a custom build may be higher (typically in the high six to low seven figures), but these systems tend to deliver the greatest long-term ROI by seamlessly integrating with the organization’s unique data ecosystem and allowing for more precise, personalized loyalty strategies.

The future of sports is smart, data-driven, and powered by AI (remember, this is The AI Playbook). By converting everyday fan interactions into actionable insights, teams can unlock a 365-day revenue engine that boosts direct sales, overall franchise values, and engagement with the organization.