Conjoint Survery Analysis: Fan Purchase Drivers
Scott Herman
Executive Summary
In November of 2016, Tom Gores made the official announcement that the Detroit Pistons Franchise would be relocating to a new venue in downtown Detroit. Construction is currently underway and the team’s new home, Little Caesars Arena, is on-schedule to be completed for the start of the 2017-18 regular season. The decision to move the franchise will bring many opportunities for the organization to generate revenue and boost profits.
Along with these opportunities comes a number of challenges that will require creative and strategic solutions in the short and long term. In order to capitalize on these opportunities, the organization will need to adapt their strategy to their new local target audience. Additionally, the organization will need to identify new methods for optimizing in-game attendance due to a completely new floor plan that brings new constraints to manage. The seating capacity at the new arena holds roughly 1,000 seats less than the previous venue, and management has placed a high priority on developing a new ticket pricing strategy in an attempt to maximize their ticket sales revenue potential for the upcoming, inaugural season. In order to develop a successful new ticket pricing plan targeted toward the preferences of our target fan base, the following questions will need to be answered:
- What arena seating attributes are most and least important to our fan base?
- What levels of these attributes are most or least desirable from the perspective of our end-users?
- What is the fan’s willingness to pay for these attributes?
Research Design
A conjoint analysis was designed with the objective of answering the questions listed above by measuring the importance across six different factors related to ticket purchasing. These factors, or attributes focused on ticket price, seating area, day of the week, box/VIP amenities, time of game, and opponent match-up. Within each of these six attributes were two to four different characteristics, or levels, that were utilized as to evaluate each factor. The product factors and characteristics used in this analysis are summarized in the following table.
| Ticket Price | Seating Area | Day of Week | Time of Game | Box/VIP | Opponent |
|---|---|---|---|---|---|
| $195 | Courtside | Friday | Afternoon | Box/VIP NO | Chicago |
| $119 | Lower Level | Saturday | Evening | Box/VIP YES | Cleveland |
| $80 | Mid Level | Sunday | Indiana | ||
| $58 | Upper Level | Mon-Thurs | Milwaukee |
To determine the fan sentiment related to these factors, a consumer survey was sent out to random sample of fan households across the Metro-Detroit population. Each respondent was asked to evaluate 16 product profile combinations, which were defined by their product attributes. The submitted ranking obtained for each product profile reveal their preferences for purchasing tickets and the corresponding factors that defined their most desirable product grouping. After collecting the results from all of the submitted surveys, the next phase of our conjoint analysis utilized regression analysis techniques. The regression model output was developed in R studio which enabled us to identify how ticket purchasing attributes affect our consumers’ purchasing decisions.
Results
The results from the survey are showcased below and illustrate the overall importance scores placed on each ticket purchasing attribute, as well as their corresponding levels. Overall, the result of this survey finds that Day of the Week is the leading factor, followed by Seating Area. Within these attributes, you’ll notice scores next to each corresponding level. These scores give insight into how the respondent might be making their purchasing decisions.Given the fact that Day of the Week, Seating Area, and Opponent all ranked far and above Ticket Price, we might assume that we have an eager target audience ready and willing to spend on watching the Pistons at Little Caeasars Arena next season. The next phase of this research study will further explore the importance of these underlying factors to put together an optimized pricing plan that will maximize revenue generated from ticket sales.
