Inside the NFL’s innovative fan data platform powered by AWS

Discover how the NFL uses AWS technology to transform fan engagement, offering personalized experiences and real-time insights through a cutting-edge data platform.

When Paul Ballew became Chief Data & Analytics Officer at the National Football League (NFL) in 2021, one of his key priorities was to develop a unified view of the League’s fans across disparate data sources. Now, that vision is a reality—enabling personalized fan experiences at an unprecedented scale.

At the heart of the NFL’s fan data initiative is a cloud-based ecosystem built on Amazon Web Services (AWS). The platform integrates a staggering 90 billion rows of fan data, with over 250 dimensions per fan, ingesting thousands of daily data feeds.

“If you think about the journey of bringing together legacy data, it’s extremely challenging,” says Ballew. “We had to stitch together disparate data silos from the teams, Leagues, partners – dealing with a lack of standards, governance, and privacy requirements. It’s been hard, but we’ve pulled it off in an unprecedented way.”

Replacing monolithic constraints with an agile ecosystem

The key, Ballew explains, was eschewing traditional one-size-fits-all approaches in favor of an open, composable ecosystem designed for flexibility and scale.

“We couldn’t have done this 20 years ago by pulling off an off-the-shelf closed environment and trying to solve the complexities,” Ballew states. “We needed an agile ecosystem allowing us to stitch together best-of-breed components.”

At the core of this ecosystem is a centralized data platform ingesting raw fan data from disparate sources into a unified “fan view”—a challenge Ballew experienced all too often in his previous manufacturing experience.

“The biggest question was whether we could actually stitch all this together,” Ballew remarks. “We’re likely the first sports league to pull this off at this scale.”

The result? A 4x increase in the fanbase the NFL can now comprehensively “see and know,” to over 70 million active fans across both League and team properties. This was achieved in 18 months, whereas the organization could previously only partially view 12 million individuals.

Driving personalization through agility at scale

But the real game-changer has been the ability to rapidly operationalize these insights across the entire fanbase, facilitators, and teams. The League can now act on unified fan intelligence to drive innovative experiences at scale—across ticketing, merchandising, live events, digital marketing and more.

“The key was enabling that combination between the League and our 32 clubs,” explains Ballew. “We were able to rapidly spin up while bringing that single view of the fan into sharp focus.” The outcome has been strong engagement and affinity across the board. Open rates for segmented campaigns have doubled or tripled. Opt-in rates are surging as personalization deepens connectivity and value exchange for fans. And it’s not just about technology or data, it’s about enhancing experiences for our fans across channels,” Ballew emphasizes.

Operationalizing fan views across consumer touchpoints

By unifying first-party fan profiles previously fragmented across disparate systems, the NFL bridges consumer identities across games, content, commerce and more.

“The organizations that will thrive are those connecting directly with consumers and personalizing experiences at scale,” Ballew explains. “You need comprehensive views to personalize across touchpoints—whether that’s merchandising, watching games, or experiencing tent-pole events like the Draft in relevant, customized ways.”

This empowers more timely, contextualized activation—enabling the League to quickly build buzz and garner opt-ins for upcoming experiences or channels. “We can now reach fans with personalized content and experiences where they are, not just where we assume they’ll be,” says Ballew. “The unified view has been transformative.”

Previously, the League’s monolithic systems gave fragmented visibility, translating to suboptimal user flows. But new state-of-the-art technologies like generative AI could unlock deeper potential.

“Advanced tech allows us to engage more meaningfully by enhancing context and relevance for each individual, and ultimately deliver more personalized value,” Ballew explains.

Prepping for a direct-to-consumer world through composable analytics

Ballew references his pre-manufacturing experience, using composable analytics at scale to drive ROI for partners and vendors. Applying these techniques to fan touchpoints similarly unlocks significant value.

“For years, we’ve pushed the envelope with advanced workflows to enhance user journeys,” he notes. “The beauty now is channeling the cloud’s agility to act on new opportunities—deploying modular data layers with limited latency, activating contextualized user insights in real time.”

Underpinning this agile operationalization is a flexible, API-driven ecosystem enabling the NFL to rapidly stitch together new capabilities—from identity resolution and consent tooling to specialized machine learning models and real-time decisioning.

The key, Ballew explains, is keeping ahead of the curve through iterative, elastic architectural scaling. “As data volumes grow, we can elastically extend use cases by composing modular data and technology capabilities. That agility will be essential for continually personalizing at scale.”

An open cloud ecosystem for personalization and scale

This transition has been revolutionary. Where previously teams deployed monolithic user flows, they now leverage a cloud-based ecosystem for iterative user intelligence and decisioning.

The architecture pairs data unification with operational simplification. The environment centralizes identity contexts and consent signals across internal systems and vendor touchpoints:

“We had to think of it as an ecosystem,” Ballew remarks. “We want to empower engineering teams to surface consented user signals for rapid decisioning – making that process seamless for scaling decisioning systems.”

Under the hood, an open cloud enables the NFL to activate emerging technology like generative AI in an iterative manner. As Ballew puts it, “The key is keeping ahead through elastic, composable backend tooling – centralizing decisioned data contexts for iterative scaling.”

This facilitates a modular approach to decisioning and machine learning (ML). Rather than monolithic decisioning systems, teams can elastically extend contextual AI workflows by stitching together module services and identity contexts.

The open architecture pairs emerging techniques like generative decisioning with operational simplicity and scale. Shared decisioning contexts harmonize with the League’s centralized approach to security, privacy, and consent obligations.

“It allows our ML decisioning systems to rapidly act on contextual signals—enabling responsive user flows with modern privacy engineering,” Ballew explains. “Decisioned user contexts power more automated experiences.”

Flexible personalization workflows

Ballew credits early engagement with AWS for enabling the rollout at cloud scale. The openness of AWS’s data plane supports integration with existing systems and emerging use cases.

“Data workloads range from 90 billion daily fan attributes ingested to millions of marketing triggers syndicated,” says Ballew. “We handled the breadth and depth in a unified way through a composable framework.”

This architectural approach pairs siloed tooling with unified governance and consent obligations. For example, consent from vendors like OneTrust is built into decisioned experiences programmatically. “It allows us to rapidly integrate workflow contexts while staying accountable to user preferences,” Ballew notes.

Tooled appropriately, enterprises can elastically integrate new systems with intelligent data workflows. AWS lets the NFL break down data silos via an agile, extensible ecosystem.

“Our environment provides end-to-end elasticity,” says Ballew. “Teams can spin up tailored APIs and operational workflows for each use case—stitching identity contexts and activating insights on demand.” At the core, shared infrastructure enables cross-pollination of emerging techniques—from recommendation AI to real-time consent flows.

Navigating direct-to-consumer opportunities with adaptability

This convergence of data ecosystems with emerging use cases empowers enterprises to scale decisioned intelligence across touchpoints and consumer journeys.

“The beauty of the cloud is to unlock opportunities we couldn’t see before,” explains Ballew. “As new channels emerge, we can bring in the right integration capabilities and activate them in a future-proofed way.”

Exposing dynamic functionality atop unified data assets enables a slew of new use cases—from consented user flows to recommendation engines and generative AI deployments.

“We’re seeing where this is going,” says Ballew. “The key will be reintegrating modular components with a flexible data ecosystem—enabling agile activation with strong governance.”

Looking ahead, elastic data refactoring capabilities will allow the League to compose emerging decisioning workflows, connect new services securely, and streamline personalization channels. For example, by composing streaming data with unified fan contexts, brands can make inferences automatically and dynamically filter outputs for target user subsets.

“Generative AI is exciting because we can further personalize and distribute content at speed,” notes Ballew. “But it starts with getting your data assets future-proofed with appropriate governance.”

With a flexible data ecosystem primed for emerging AI and ML services, the NFL looks to unlock future opportunities.