One business strategy that is finally gaining traction in sports is dynamic pricing. Associated with a poor connotation to users of Uber and Lyft, dynamic pricing, which is also referred to as surge pricing, is a pricing strategy in which businesses set their prices for products or service based on current market demands. This real-time pricing strategy is not a new concept. Travel-related industries such as hotels, rental cars, and airlines have employed this technique for years, as well as more recently in the energy market and sports businesses.
In 2014, Cubs single-game ticket prices at Wrigley Field were set through dynamic pricing, which helped more accurately price tickets for individual games and provides fans with more price options. However, with football season finally back, we decided to look at how a dynamic pricing structure could work for an NFL team. Back in April, the Buffalo Bills announced a new dynamic ticket pricing model for all Bills home games in the 2017 regular season that will adjust ticket prices to better reflect demand throughout the season. With this precedent established, we decided to see how this economic strategy would work for the Houston Texans.
The static pricing structure currently employed at NRG Stadium, formerly known as Reliant Stadium, is almost inherently obsolete. While the Houston Texans are making plenty of money, a dynamic pricing structure could further increase the amount of money made as they more efficiently maximize their customer’s willingness to pay. For instance, ever since the 2002 expansion and conference realignment by the NFL put a new team into Houston, the Texans have had an intense rivalry with the Tennessee Titans, as they were once the Houston Oilers. Texans fans are obsessed with this rivalry, and would probably be more willing to spend higher prices to see the Texans play the Titans than say the Cleveland Browns.
To determine how much a customer would be willing to spend on various attributes, we set up a survey. Each question was comprised of a different set of attributes, and fans selected which ticket they would prefer to buy. We ran this survey through a few dozen fans, across Twitter and our other connections, and managed to obtain an average ranking for each question. We then performed a conjoint analysis on this data.
Conjoint analysis is a survey based statistical technique used in market research that helps determine how people value different attributes that make up an individual product or service. By analyzing how our respondents make preferences between these various ticket options, the implicit valuation of the individual elements making up the ticket can be determined. These implicit valuations are called utilities or part-worths and can be assigned a dollar value, which can be used to create market models to estimate revenue and profitability of new designs.
Our conjoint analysis survey focused included four attributes, the seating level, price, month of the game, and the team played. We wanted to focus on the team played as we felt that this is where the Texans could profit the most from a dynamic pricing structure. Additionally, while a price difference between the three seating levels already exists, this survey should validate if those price discrepancies are too much or little compared to the customer’s willingness to pay. Here are our findings…
While ticket price and the seating area were the most important attributes, it is interesting to note that the team played against followed close behind. Most customers want to pay the least for the best seats, naturally, but as we suspected, the Titans had the greatest amount of increased part-worths. Our calculations showed that the typical fan will be willing to pay $30 more per ticket, independent of the seat, to see the Texans play the Titans as opposed to the Browns. Perhaps unsurprisingly, the other two teams in their division, the Colts, and the Jaguars, also netted positive part-worths. Additionally, the Browns and 49ers netted negative part-worths.
The two teams outside of their division not named the Browns and 49ers that the Texans play at home in 2017, the Steelers and the Cardinals, had the most interesting results. The Steelers had a positive part-worth, and fans are expected to pay $16.50 more to see the Texans play them, as opposed to the Browns. However, the Cardinals had a negative part-worth, and the typical fan only valued seeing them $3 more than the Browns.
By dynamically pricing the tickets higher for games against their division, as well as the Steelers, the Texans should be able to increase our profits by selling closer to the customer’s expected willingness-to-pay. Additionally, by selling the most expensive tickets when they play the Titans, they will be able to make over twice as much than if the Texans held them the same price for a typical game. Each visiting team has an established reputation and historical rivalry with the home team, which should be considered in conjunction with that team’s brand equity in this context. By exploiting those margins, the Houston Texans should expect a generous rise in profits.
As teams continue to find new ways to maximize their revenue streams, we should expect dynamic pricing in sports to further gain traction as more sports businesses take advantage of this technology. What do you think? Are you against dynamic pricing as a customer? How has it affected you? Let us know in the comments below! And as always, our code can be found on Github.
The SaberSmart Team