How the Philadelphia 76ers Win Off the Court Using Machine Learning from DataRobot
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- DataRobot Enterprise AI platform
Tech Stack
- Machine Learning
- Predictive Modeling
- Data Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Revenue Growth
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Predictive Analytics
- Analytics & Modeling - Machine Learning
Applicable Functions
- Sales & Marketing
Use Cases
- Predictive Replenishment
Services
- Data Science Services
About The Customer
The Philadelphia 76ers are a professional basketball team in the National Basketball Association (NBA). They are owned by Harris Blitzer Sports & Entertainment (HBSE), who also own the New Jersey Devils of the National Hockey League, among other sports and entertainment properties. The 76ers are considered a rising powerhouse in the NBA and are one of the most popular teams among fans in Philadelphia and around the world. The organization is known for its strong focus on data analytics, using data to inform decision-making processes across all levels. The 76ers' Analytics Team is constantly looking for ways to be more efficient with its work and make its data-driven process more dynamic.
The Challenge
The Philadelphia 76ers, a professional basketball team in the NBA, is part of a new wave of sports franchises that are leveraging data analytics to optimize both their on-court performance and business operations. The organization has a strong focus on using data to inform decision-making processes across all levels. One of the key challenges faced by the 76ers' Analytics Team was improving the efficiency of their season ticket renewal process. The team had been using data science and simple modeling techniques, but lacked a dynamic machine learning tool that could adapt and learn as more data was collected. This meant that the team had to do a lot of work in the offseason to produce a static model. The goal was to transform the renewal process from a once-a-year event into a year-round retention process.
The Solution
To address this challenge, the 76ers Analytics Team turned to DataRobot's Enterprise AI platform to improve its modeling process for season ticket renewals. The platform allowed the team to build dynamic, predictive machine learning models that could track, measure, and analyze data throughout the year. This enabled the team to identify at-risk accounts and factors that most influenced renewal. The models also helped the sales renewal team optimize its process by prioritizing their time and focusing more diligently on higher-risk accounts. Looking ahead, the 76ers Analytics Team plans to expand its use of machine learning and predictive modeling to other parts of the business, such as improving lead scoring and targeting fans with better offers. They also plan to scale their work and apply it to other sports franchises under the Harris Blitzer Sports & Entertainment umbrella.
Operational Impact
Quantitative Benefit
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