This paper covers the HBS Nor'Easters case. The objective is to maximize total revenue for a minor league baseball team, requiring an estimation of demand at different ticket and price categories, and striking a balance between gate and concession revenues.
¶ … Easters
Identification of Issues
The Springfield Nor'Easters are a new minor league baseball team in Springfield, MA. They are 1 1/2 years away from opening night and are trying to finalize their business model and pricing structure. There are a number of factors that the team will need to take into account with respect to setting its ticket prices. The team must consider whether or not it wants to emphasize season ticket sales, or individual ticket sales. The size of the local market and how much of that market the team can capture should also need to be taken into consideration. Competition is another factor for the team to consider. In addition, the split between gate revenues and concession revenues is another factor. The solution will be the one that delivers the highest total revenue, not the highest gate revenue. The more the team charges at the gate, the fewer customers it will have, and the lower the concession sales will be. This points to a theory that the optimal ticketing structure will be the highest possible price that will ensure a sellout every night. A complicating factor is that some season ticket holders will not attend every game, reducing concession opportunities on those nights.
Without gate or concession revenues, the team's budget shortfall is around $1 million (see Exhibit A). The ticket policy needs to put the team in a position to earn that. The team has 38 home games and 3600 total tickets for each game, for a total of 136,800 as the maximum possible attendance for the season. The breakeven point, therefore is, $7.36 per person in combined gate/concession, assuming full attendance. At the most basic, the team needs to assess whether it can achieve full attendance and earn that much money. If need, the Nor'Easters need to consider folding operations.
Analysis and Evaluation
A SWOT analysis can help understand some of the fundamentals concerning the market and the team. The team's core strength lies in the popularity of baseball. According to the survey, 38% of residents claimed to be baseball fans, with 28% having attended a game in the past year. Given the distance to Boston, that 28% is an encouraging figure -- those who are fans are dedicated. The team is likely to have low ticket prices and only plays during the summer months when the weather is Springfield is mild and pleasant. There are two key weaknesses. The first is that the team is new. The Nor'Easters are starting from scratch with respect to building their brand. 'A' ball is also a weakness, because the players are not known to the fans, and will change every year. This makes it harder for the club to build a relationship with the fans because that relationship is going to be based on the club and the sport, rather than individual stars and personalities on the team. Also, the team does not yet know what its major league affiliate will be. There will be more fan interest if the Red Sox are the affiliate than if a team from outside the area is sending players to Springfield.
There are a few good opportunities, however. There is little competition in the market. The minor league hockey team may be leaving, and regardless its season does not overlap with that of the Nor'Easters. The main competition comes from other forms of entertainment, which range from watching television to any outdoor family event in the region. Some minor league clubs seem to make a substantial amount of their money on concessions, which is encouraging because it raises the possibility of dual revenue streams for the club (gate and concession). The team may also be able to raise radio broadcast rights as a means of not only building the brand but generating a little bit of extra revenue as well. There are some threats to consider, however. One key threat is the state of the economy. Attending baseballs games is a discretionary expense. Springfield, it seems, is a city with a relatively stagnant economy and population size. Thus, it should be expected that there will be a correlation between local economic indicators (unemployment, consumer spending, percent of population below the poverty line) and demand for baseball tickets. Other threats come from the team's partners. Failure to find a major league partner would surely doom the club. It could also face financial pressure from the college if parking revenues are insufficient, or from a decline in sponsor funding as well. The financial model, therefore should assume no sponsorship dollars and be built around earning a profit without them.
In the financial analysis, the first thing to consider is the total market size. Springfield is a small city in central Massachusetts. The urban market is 155,000 (not 55,000) and the metro area has 700,000 people, according to the U.S. Census Bureau. If the town only had 55,000 people, the total market would not be big enough -- every man, woman and child would need to attend three games person to meet capacity and that is not even remotely realistic. These population figures, however, do not represent the total market. It can be assumed that the population below the poverty line is not going to be able afford family nights out at the baseball game -- this brings the total market size down to 116,250 in the city. Children cannot be discounted, however. Although they are not the purchasers of the product, they are expected to comprise a significant portion of end users. That Springfield has the highest percentage of children in the state is encouraging as families are a core target market.
An analysis of the survey results is revealing, and is going to prove critical to the development of the ticket pricing matrix. The underlying assumption of this analysis is that the survey results can be taken at face value. There were 651 respondents to the survey, and they roughly tracked the city's demographics. There were slightly more families among survey respondents, and slightly fewer below the poverty line. In general, the survey results can be taken as statistically valid. However, the pricing matrix that is decided upon should be subjected to sensitivity analysis to ensure that the proposed matrix is profitable even if actual sales fail to meet projections.
The first thing that jumps out is that 2% of respondents indicated that they might buy a season ticket -- this is 2325 people out of the target market. This indicates that the team could have a healthy season ticket base. A total of 45,337 people indicated that they might attend at least one game. This is also encouraging. Just on these broad strokes, it appears that there is a market for 'A' baseball in Springfield if the price points are reasonable.
In the survey, the concession revenues question was not asked in relation to ticket prices, or the size of the ticket package. As a result, the estimated concession sales from each ticket should be taken conservatively. Season ticket holders are likely to spend less per game, because they are attending most games, and if ticket prices are at the high end this could lower concession revenues. The margin expected on concessions is 39%. A weighted average can be taken to determine the average gross concessions per ticket: (11% * $4) + (45% * 6) + (36% * $11) = $7.10. This equates to $2.77 net. The breakeven point has been established as $7.36 per ticket assuming a sold out season, so ticket prices must average at least $4.59 in order for the team to breakeven. That must be taken into consideration when setting season ticket prices in particular. It looks as though there is sufficient demand -- 2325 people in Springfield or 10,500 in the metro area could be interested in season tickets, so the demand looks to be sufficiently high to enjoy a capacity season if the prices are within the range consumers want to pay. For the purposes of this analysis, it will be assumed that all tickets (grandstand and bleacher) will cost the same. Although consumers are willing to pay a little bit more for a grandstand seat, few consumers are willing to pay more than 10% more. This indicates that there is very little preference among consumers between the two options. The small size of the stadium -- ensuring good views for all -- may be a factor in the relative lack of preference.
To determine the highest price whereby the team can expect a sold out season, the starting point should be the season ticket base. If we base demand strictly on the city limits population, approximately 56% of the 2% interested in season tickets would pay $6. Using this as a starting point, we derive the matrix is Exhibit B. This matrix shows that almost all of the ticket sold will be 38- and 20-game packs. A small number of single tickets will be available. At this level, the baseball team will turn a profit. However, the objective is to maximize profit.
By increasing the prices, the team will essentially be focusing on the high end of the market. The market research indicates that 24,412 people will attend a single game. They would do so even at the high end ticket price of $14. Using that as a starting point, the matrix skews towards high prices. The question is whether charging high prices is likely to maximize attendance. In this scenario, single tickets would be 24,412 in number at the $14 price. There would be 4986 five-game packs sold at the $12 price. Built into this matrix is the assumption that the team would like to have a strong season ticket base as that represents guaranteed revenue. Thus, the team may choose not to offer the 20-game pack. Indeed, the 20-game pack is logistically challenging anyway, as the team would need to have pre-set games for that pack in order to ensure that all games were sold out, that certain games were not subject to demand far in excess of capacity. The resulting matrix is found in Exhibit C. Note that in this scenario, the team does need to sell 20-game packs in order to ensure a sold out season. They would do so at the $10 level. This is because season tickets sold at a 40% discount would be sold at the $8 level.
The second matrix represents the profit maximization matrix, because it maximizes ticket prices. The constraints are the demand at each level for tickets at that price level. This matrix delivers total revenues of $1.83 million, for a profit of $824,977. This should be the maximum profit level. From a business perspective, this mix of tickets also allows the team to have a small season ticket base, a healthy half-season ticket base, and still leave room for over 600 walk-up or single-game tickets each game. Having a mix of ticket types, each at reasonable numbers, is essential for encouraging consumers to purchase.
It is worth noting that the Nor'Easters are going to be predominantly reliant on gate revenues under either scenario. The survey results indicate that the Springfield market is not likely to spend heavily on concessions. The team could entice them to spend more by offering a wide variety of concessions, and some higher margin offerings. However, if the survey results are taken at face value the people of Springfield are far more likely to spend their money on tickets than they are on concessions.
It is worth considering, however, that two-thirds of the survey respondents are from core markets (baseball families, minor league sports fans) rather than the general population. Therefore, it is difficult to extrapolate the survey results to the broader population. Overall interest in the baseball tickets might be lower than these estimates show. This is why the matrix needs to be subject to strong sensitivity analysis. For example, if the demand numbers are shifted down a dollar category in each case, from the Exhibit C. scenario, the team's profit will be $551,377. This indicates that there is some flexibility within these targets that should the team be forced to lower prices in order to fill the stadium, it will be able to do so. However, the Nor'Easters could also draw from the surrounding area, with a metro population of 700,000. This means that the projections are probably understated, rather than overstated. The stadium is very small for the size of the city, and this means that there should be surplus demand if the team is marketed well.
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