For the Philadelphia 76ers, data is an integral part of how they work, helping them make strategic decisions on both the sports and corporate sides of the organization. On the business side, they knew that taking a data-driven approach could help them become much more efficient in how they approach their ticket sales process. Enter automated machine learning with the layup. With DataRobot’s platform, the 76ers were able to make a big impact, helping their sales team use their data in a way that is much more dynamic and resourceful.
Like any sports organization, the 76ers are focused on season ticket holders. In their case, this includes not only growing their ticket holder base but also retaining the season ticket holders that they already have. For their salespeople, knowing which customers to call first is a key part of the sales cycle. This step can make a difference in whether or not they meet their sales quota.
The 76ers Analytics team was able to build predictive models with DataRobot that helped their salespeople better prioritize the order of their calls. Because this made their operations more efficient, it freed up time for the sales team to focus on other priorities, such as targeting and winning higher risk accounts. Predictive modeling turned the renewal and retention cycle process from an annual scramble into a much more strategic, year-round process.
Their success with the sales team has implications for the rest of the organization. Because the 76ers fall under the Harris Blitzer Sports & Entertainment (HBSE) umbrella, they plan to replicate this data-driven approach with other HBSE teams.
To learn more about how the Philadelphia 76ers won big with DataRobot’s automated machine learning platform, download the case study.