From Stats to Stands: Leveraging Big Data to Elevate the Fan Experience

Having been involved in the sports analytics community for over six years, I have witnessed significant advancements in how teams utilize data and artificial intelligence (AI) to inform both strategic business decisions and on-field performance.

Sports organizations are continuously evolving their approach to fan engagement, recognizing the pivotal role it plays in driving revenue through avenues such as sponsorships, merchandise sales, venue spending, and subscriptions. In order to further grow the fan base, there has been a notable shift towards personalized interactions, yielding substantial dividends in terms of engagement and revenue generation, as evidenced by recent achievements across various leagues…

• During the 2022-23 NBA regular season, there was a remarkable surge in engagement across the NBA App, NBA League Pass, and NBA social media accounts. Notably, the NBA's presence on Instagram amassed over 13 billion video views, the most of any account on the platform.
• The NHL witnessed record-breaking cable viewership during the 2023-24 season, with notable engagement spikes across all social media platforms, exemplified by the Boston Bruins' significant user activity (~30.6M TE).
• Landmark events like the most recent Super Bowl, featuring the Chiefs and 49ers, drew the largest television audience in history (over 123M viewers), and 88 out of the top 100 most-watched TV broadcasts in the U.S. in 2022 were NFL games.?

These achievements owe much to the transformative capabilities of data analytics technologies, which enable teams to gain deeper insights into fan behavior, enhance in-stadium experiences, and deliver personalized content tailored to individual preferences.?

However, personalizing fan engagement presents a multifaceted challenge exacerbated by the vast amount of data from diverse channels, alongside the constantly shifting landscape of consumer preferences. Creating a unified view of this data to derive actionable insights is inherently complex, requiring robust infrastructure and analytics capabilities to process and analyze all the data from a variety of sources.

In this article, I cover how certain teams and leagues are leveraging data to elevate the fan experience and highlight key technologies driving these innovations today and in the future.

Enhancing the In-Stadium Experience

With an average of over 100 million fans attending major league games annually, optimizing the in-stadium experience is paramount for teams. Achieving this requires a robust data infrastructure capable of integrating real-time data feeds from various sources to provide comprehensive insights into fan behavior.

One exemplary case is the Detroit Lions, who have pioneered the use of analytics to personalize the in-stadium experience for their fans. At SBJ Tech Week, Ashton Mullinix shared how they developed an in-house analytics war room, where they are able to track fan interactions from ticket purchase to seating, enabling them to implement initiatives such as optimizing zone capacities, redirecting crowds to alleviate bottlenecks, providing real-time concession information, and enhancing sponsorship activations.?

Digital Content Innovation

In the realm of digital content, Generative AI has emerged as a pivotal technology for engaging fans on a global scale. Leagues like MLB leverage advanced analytics to curate personalized content through features like the Film Room, which delivers custom reels enriched with statistical insights gathered via Statcast. Additionally, AI-driven celebrations are employed to create highlights for marketing purposes, while real-time translation capabilities expand the reach of broadcasts to diverse audiences worldwide.

Also a specific way the NHL is looking to engage with the next generation of fans is through its Power Players youth advisory board. Debuted in 2019, the program provides youngsters aged between 13 and 17 with a platform to voice their opinions on how the league’s digital content and marketing campaigns can be more relevant to their demographic.

Sales and Marketing Strategies

Data-driven predictive models play a crucial role in personalizing fan engagement strategies. By employing techniques such as uplift modeling and predictive Customer Lifetime Value (CLTV) analysis, teams can tailor marketing efforts more effectively, identifying the most receptive audience segments and crafting compelling narratives that resonate with individual fans.

Technological Enablers

A range of advanced technologies has democratized data analytics, empowering teams to extract actionable insights efficiently. Platforms such as Databricks offer comprehensive data unification and processing capabilities, while cloud services like AWS and Microsoft Azure provide scalable solutions for data storage, analysis, and visualization. Outlined below are some of the technologies, features, and benefits that teams are using today, which are acting as the foundation to their data strategy:?

Databricks:

• Key Features: Unified platform for Data engineering, analytics and Machine learning, real-time streaming data processing capabilities, share and discover data products securely and efficiently through Delta Sharing.?
• Benefits: Simplifies data handling by unifying various data types, supports multiple programming languages for enhanced flexibility, and based on open-source technologies which helps avoid vendor lock-in.

Snowflake:

• Key Features: Snowgrid for data sharing and collaboration, Streaming Pipelines for unified stream and batch processing.
• Benefits: Enables seamless collaboration without the need for ETL processes, provides a unified architecture for stream and batch processing, automates scaling to handle varying workloads efficiently.

AWS:

• Key Features: Amazon Redshift for SQL-based data analysis, Amazon Personalize for personalized recommendations, and Amazon QuickSight for interactive insights.
• Benefits: AWS enables comprehensive data analysis across various data sources, integrates machine learning for personalized fan experiences, and offers interactive dashboards and reports for actionable insights - 100+ individual services for data teams to leverage.

Microsoft Azure:

• Key Features: Azure Data Lake for accommodating heterogeneous data sources, Azure Data Factory for data ingestion and processing, PowerBI for immersive visual insights.
• Benefits: Supports diverse data formats for seamless integration, streamlines data ingestion and processing workflows, transforms data into visually appealing and interactive insights.

In conclusion, the intersection of data analytics and fan engagement represents a dynamic frontier for sports organizations, offering unprecedented opportunities to deepen connections with audiences while driving growth. By leveraging innovative technologies and embracing data-driven strategies, teams can cultivate vibrant fan communities that transcend traditional boundaries, ushering in a new era of sports fandom.

At Blue Orange Digital, we’ve helped organizations drive additional revenue by applying advanced analytics, custom integrations, and data engineering workflows within their data architecture in order for teams to leverage their data effectively.

If you’d like to discuss strategies and further understand how teams are leveraging analytics to improve fan engagement, let's connect!