Case Study: Predicting Event Attendance to Improve Planning & Drive Revenue
Association Challenge: How can we predict attendance so we can improve event planning and drive revenue?
The association's annual conference was its largest source of revenue. They used email campaigns and direct mail to stay in touch with prospective attendees, but were unable to confidently estimate expected attendance, registration costs, venue amenities needed, on site staffing levels, and more.
Association Analytics Solution: Collect all critical event data in a central location and create data visualizations
Association Analytics implemented a data warehouse and created data marts. The data warehouse contains key information from several disparate sources. It became the single source for event-related data, including customer information, past event attendance, membership history, committee participation, key demographics, and engagement factors.
Visualizations were built in Tableau on top of the data mart that allowed the association to see their member behavior in a new way.
Association Analytics also provided training and support for association staff to ensure successful adoption.
The customized dashboards and advanced predictive analytics enabled the association to better understand their member’s behavior. Based on that information, the association improved target marketing and outreach. They were also able to better predict attendance and profit for future conferences.
The data visualizations inspired critical problem-solving and experimentation to help grow events revenue. For example, data analysis showed travel distances over 500 miles were a barrier for 85% of potential attendees. The decision was made to experiment with two annual conferences to minimize travel.