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Beyond Lifetime Value: A Customer Journey Analysis to Fan Engagement and Spending in Professional Sports

Author(s)
Antonakakis, Christina Elizabeth
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Advisor
Chase, Christina
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In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/
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Abstract
This research examines engagement and spending behaviors in a professional sports ecosystem, introducing Customer Journey Analysis (CJA) as a dynamic alternative to traditional customer lifetime value (LTV) models. Through an analysis of over 930,000 net new fans acquired from July 1, 2021, to June 30, 2024, this study identifies critical patterns in acquisition channels, spending behaviors, and engagement metrics over multiple seasons. Notably, the findings highlight the significant influence of early touchpoints, such as ticket purchases and email interactions, on fan progression. Metrics like email open rates and multi-channel engagement emerge as strong predictors of future spending, revealing nuanced insights into fan behavior. This research emphasizes the importance of integrating behavioral and financial metrics to sustain fan involvement. By transitioning from static LTV models to a multi-dimensional CJA framework, actionable strategies are proposed for optimizing engagement channels, improving retention, and driving long-term revenue growth. Key findings reveal that predictive modeling and customer segmentation analysis are instrumental in identifying high-potential fans and distinct audience profiles. Tailored retention strategies, including personalized follow-ups and exclusive engagement incentives, address churn risks while fostering ramp-up and loyalty across diverse fan groups. Future work should explore tenured fan behaviors and incorporate diverse data sources, such as in-venue spending and team performance metrics, to deepen understanding of fan evolution across different lifecycle stages.
Date issued
2025-02
URI
https://hdl.handle.net/1721.1/159093
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology

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