Major League Soccer Analytics 50 Submission
Major League Soccer
New York, NY
Major League Soccer aimed to maintain and increase a broad base of supportive fans—an important component in the success of each sports team. MLS’ goal was to foster and nurture fan affinity by enhancing efforts using marketing analytics.
The organization developed a four-phase predictive analytics approach to move fans from one phase to the next, based on a series of activities.
- Data acquisition: The goal of the first phase was to collect information and other attributes that will help establish and enhance the relationship with the fan.
- Fan engagement: Communications with the fan base became more personalized, based on enhanced fan profiles as a result of the data acquisition. Fan communication is driven by “Fan Journey” across various channels (email, paid digital/social, SMS, app notification) leveraging different data variables (location, club preference, click data, custom scores, etc.).
- Monetization: Based on fan profiles and transaction histories, MLS used predictive analytics to identify the best offers for customers in an effort to increase ticket, merchandise and digital subscription sales.
- Loyalty: MLS utilized fan behavior data to identify the club affinity, which showed a strong correlation with engagements. An increase in engagements leads to an increase in monetization and, ultimately, an increase in customer lifetime value.
Based on email response data, the personalized email approach yielded a 39% increase in unique click rate versus the static email. In addition, sales per email increased by 234% when offers were personalized to the recipient based on key attributes identified through predictive analytics.