Case Study Springfield Nor Easters

The Springfield Nor’easters: Maximizing Revenues in the Minor Leagues Case Analysis

Grace Chan 996834207 Date Submitted: November 4th, 2010 Date Due: November 4th, 2010 1. (5 points) What are the decision problems and research problems for the survey conducted (Exhibit 5)? Decision Problems: * How should we price and package different types of tickets to properly maximize
received revenues from different types of consumers? * How price sensitive are our target consumers? Who are our target consumers? Research Problems: * How does the demographic of the Boston area affect attendance for sporting events? * Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? * What are the consumption patterns of consumers in terms of trade offs between pricing of tickets, structuring of multiple-ticket packages, revenue yield from concessions? 2. (10 points) Evaluate the survey in Exhibit 5: Was the questionnaire designed properly? Discuss information collected, design of individual questions, and survey structure. The information collected from this survey was able to directly address several questions from that apply to the research problems (see Figure A).
From this we can derive that overall, in Springfield (assuming that the sample is representative of the population), 38% of residents do have some interest in baseball, but only 28% of the residents have ever attended a professional baseball game. Out of this only 17% of the population have attended at least one minor-league game in the last 2-3 years, however 39% of the residents would be willing to attend at least one game if a minor league baseball team ever came to Springfield. Insight about grand stand tickets was also collected, indicating that 72% of the population is not willing to pay more than a 10% premium over regular bleacher seats for a grand stand seat, hinting that there may be no opportunity to explore in terms of multi-priced seating. Another insight that can be drawn from the survey is that 81% of those who attend a game would be willing to pay $6 or more on various concessions per person. 56% of those surveyed were female and 66% of those surveyed lived with at least one child between the ages of 5-16, which may indicate that child-ticket pricing may be exploited. In addition, the sequence of questions did follow the typical “qualifying questions, warm-ups, transitions, difficult and complicated questions, and finally, classification & demographics questions”
order. However when it came to the willingness-to-pay for the different types of tickets themselves, there are some problems that Buckingham did not foresee when distributing this survey. One of the major problems was with how the pricing question was presented. First, the question itself was worded in a way that made little intuitive sense: asking the customer what they would be willing to pay per game, instead of asking their maximum willingness-to-pay (e.g. someone who is willing to pay $10 for a game would be willing to pay $4 as well.) Next, the categories of people indicating their willingness-to-pay are also not very clear. There is no way to distinguish who is willing to pay a certain price for a certain type of ticket. For instance, if someone had indicated they were willing to pay $10 for a single game ticket, but earlier stated they would to subscribe to a 38-game full season, the answer they provide for prices regarding single ticket games, 5-ticket games, and 20-ticket games becomes useless, and distorts the actual prices people are willing to pay for these tickets. In addition, the categories for the answers utilized block numbers, giving people the option to choose certain prices, but noting in between (e.g. the category $4 and $6 is available but any price between $4 -$6 is not an option and data is not collectable for this category). In addition, the minimum range for prices was listed as “Less than $4” providing a range that could go from $0 - $4 and did not gather meaningful data about these consumers. There were also some irrelevant questions, such as #3 - $6 (Questions concerning sports overall: too broad, not specific for baseball.) and #17 (Education information) that added no value to the survey. 3. (6 points) Evaluate the survey in Exhibit 5: Was the sampling strategy proper? Buckingham had chosen to mail out 10 000 postcards inviting the recipients to go online and fill out the survey. These 10 000 postcards were mailed out to 2 pools of people: the first 5000 being general members of the Springfield community taken from a census, who earn an income above the poverty line. The second list of 5000 names was obtained from sports-related organizations in Springfield who were asked to supply a random sample of names from its database. Buckingham had stated, however, that he wanted to attract all types of individuals to view the games. Not simply just sports enthusiasts and families of those who were playing, but also casual fans and people who show up for pure entertainment. Yet when choosing his sample, 50% of those selected came off of a list of people known to enjoy sports and have previous experiences attending sporting events or have children enrolled in sports. With a heavier weight on sports fans, this potentially distorts the information collected from the survey in regards to sports attendance rates and willingness-to-pay for sporting events. As seen in Exhibit 5, the survey was completed by a marginally larger amount of females than males, in addition to several parents of young children. 4. (20 points) Based on survey results, design a ticket-pricing plan for the Nor’easters’ first season. You may use Exhibit 6 as the template to work your analysis. (Please refer to Figure B) Based on the survey, the following optimal prices for tickets are $10 for one-game tickets, $40 for five-game tickets, $120 for 20-game tickets, and $228 for full season tickets. The average person will spend $8.56 per game. With this model, the ticket prices are set at a reasonably low price, within the typical minor league range of $6 - $26, but still above the college prices ($5 - $6) to give it some prestige. The price for a single game also rivals the price of close substitutes for entertainment like going to the movies. If we assume that the sample is, indeed, representative of the population, we can use the survey data to calculate projected profit. Ticket revenue is calculated by multiplying the dollar amount received per ticket sold by the number of tickets bought. Concession revenues is calculated by taking the number of tickets bought per category, multiplied by the number of expected games they will attend and finally multiplied by the amount one person is expected to spend per game ($8.56). Donations received total to $46 000. Fixed expenses amount to $1051879, after deducting subsidies made by the major league. Overall, the Springfield Nor’easters are expected to turn a profit of approximately $118705.10 if all the assumptions made are valid. 5. (9 points) If you have access to survey data, suggest three cross-tabulations you may want to create. Explain how these three cross-tabulations may help address research questions.
Results from Question 7 (If a minor league baseball team came to Springfield, is it likely you would…) vs. Question 8 - 10 (If you were to attend a _____ game, what would you be willing to pay?)
As mentioned above, there are problems with the way the data from the survey is presented, as it is ambiguous which sets of users are giving input about the different prices per category. Potentially, someone who said they would never attend a game could have answered that they would be willing to pay $8 per game for a 38-game ticket, yet when tickets actually go on sale, they would not purchase at all, distorting our analyses. If we were able to cross-tabulate items such as those actually willing to purchase a ticket and their different willingness-to-pay for each price level, it would allow Buckingham to determine more realistically how much people are willing to pay and discover their underlying price sensitivities. (Question 14, 16) Age/Number of children and whether they would be willing to attend a minor-league game in Springfield for baseball (Question 7)
This helps uncover patterns between the demographic of the sample and their different purchasing patterns and in addition, helps distinguish different segments of potential customers. There may be some correlations between the age of an individual and how often they would attend a game, which could then lead to insights about the typical income an individual in any age category earns and implications about how much they would want to pay for a ticket. For example, those that are young adults may be too busy to attend a full season of minor league baseball but may want to attend a couple games once in a while with friends and could act as a potential target market. In addition, patterns can also be uncovered between individuals with children in their families and the number of games that they are interested in attending.
What type of ticket they want to purchase (or based on price) versus how much they expect to spend at one game on concessions
As mentioned in the case, Buckingham did want to uncover information about the importance of concession sales as a percentage of revenues for a minor-league team. Cross-tabulating these two categories can correlate purchasing habits between the number of games any individual may attend, and how much they feel is appropriate to spend on concessions per game. As a result, this can also help uncover insight about trade-offs between concession sales and ticket pricing: if individuals have a low willingness-to-pay per game but indicate high consumption patterns for concessions, Buckingham can develop a plan that will offer cheaper seasonal ticket prices, at the expectation they will be spending more money on the location. The same could happen in reverse.
APPENDIX

FIGURE A | Question | Decision or Research Problem Addressed | Question Category | 1 | Do people have any interest in watching minor-league baseball? | Screener | 2 | Do people have any interest in watching minor-league baseball? | Screener | 3 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? | Warm-up | 4 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? | Warm-up | 5 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? | Warm-up | 6 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? | Warm-up | 7 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? | Transition | 8 | How should we price and package different types of tickets to properly maximize received revenues from different types of consumers? What are the consumption patterns of consumers in terms of trade offs between pricing of tickets, structuring of multiple-ticket packages, revenue yield from concessions? | Difficult and Complicated | 9 | How should we price and package different types of tickets to properly maximize received revenues from different types of consumers? What are the consumption patterns of consumers in terms of trade offs between pricing of tickets, structuring of multiple-ticket packages, revenue yield from concessions? | Difficult and Complicated | 10 | How should we price and package different types of tickets to properly maximize received revenues from different types of consumers? What are the consumption patterns of consumers in terms of trade offs between pricing of tickets, structuring of multiple-ticket packages, revenue yield from concessions? | Difficult and Complicated | 11 | How should we price and package different types of tickets to properly maximize received revenues from different types of consumers? What are the consumption patterns of consumers in terms of trade offs between pricing of tickets, structuring of multiple-ticket packages, revenue yield from concessions? | Difficult and Complicated | 12 | How should we price and package different types of tickets to properly maximize received revenues from different types of consumers? What are the consumption patterns of consumers in terms of trade offs between pricing of tickets, structuring of multiple-ticket packages, revenue yield from concessions? | Difficult and Complicated | 13 | How should we price and package different types of tickets to properly maximize received revenues from different types of consumers? What are the consumption patterns of consumers in terms of trade offs between pricing of tickets, structuring of multiple-ticket packages, revenue yield from concessions? | Difficult and Complicated | 14 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? How does the demographic of the Boston area affect attendance for sporting events? Who are our target consumers? | Classifications and Demographics | 15 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? How does the demographic of the Boston area affect attendance for sporting events? Who are our target consumers? | Classifications and Demographics | 16 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? How does the demographic of the Boston area affect attendance for sporting events? Who are our target consumers? | Classifications and Demographics | 17 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? How does the demographic of the Boston area affect attendance for sporting events? Who are our target consumers? | Classifications and Demographics | 18 | Do people have any interest in watching minor-league baseball, and if so, is this factor affected by other aspects such as demography (i.e. age, income, etc.)? How does the demographic of the Boston area affect attendance for sporting events? How price sensitive are our target consumers? Who are our target consumers? | Classifications and Demographics |

FIGURE B | In order to approach this question, I had to make some simplifying assumptions to make the model work: * Sample is truly representative of population * Those who said they would attend a game are indifferent about which game they attend during the year * Assume that the percentages of prices that people are willing to pay for different types of tickets will apply to the percentage of the sample interested in buying the ticket. Number of Springfield Residents Interested in Purchasing Tickets | Not attend at all | Only attend 1 game | Only attend 5 games | Only attend 20 games | Only attend 38 games | | 33756 | 11621 | 6087 | 2767 | 1107 | Numbers are calculated by multiplying the corresponding percentages in survey question #7 by the population of Springfield (55 338). Tickets Ticket Type | | Less than $4 | $4 | $6 | $8 | $10 | $12 | $14 | SINGLE TICKET | Percentage that would attend | 100% | 100% | 98% | 93% | 80% | 49% | 22% | | Revenue Per Ticket | $ < 4 | $4 | $5.88 | $7.44 | $8 | $5.88 | $3.08 | 5-GAME TICKET | Percentage that would purchase | 100% | 99% | 97% | 94% | 75% | 39% | 5% | | Revenue Per Ticket | $ < 4 | $3.96 | $5.82 | $7.52 | $7.50 | $4.68 | $0.70 | 20-GAME TICKET SEASON | Percentage that would purchase | 100% | 99% | 92% | 69% | 41% | 16% | 1% | | Revenue Per Ticket | $ < 4 | $3.96 | $5.52 | $5.52 | $4.1 | $1.92 | $0.14 | 38-GAME TICKET SEASON | Percentage that would purchase | 100% | 82% | 56% | 36% | 22% | 11% | 1% | | Revenue Per Ticket | $ < 4 (If set at $3.99) | $3.28 | $3.36 | $2.88 | $2.20 | $1.32 | $0.14 | Summary of Optimal Ticket Prices & Projected Revenue | Optimal Price Per Game | Percentage that would Purchase | Revenue per Ticket | Total Revenue | Single Game Ticket | $10 | 80% | $8 | $8 * 11621 = $92968 | 5-Game Ticket | $8 | 94% | $7.52 * 5 = $37.6 | $37.6 * 6087 = $228871.20 | 20-Game Ticket | $6 or $8 (Note: there is no information for how much demand there would be for $7, so for simplification purposes, I chose to use $6) | 92% | $5.52 * 20 = $110.40 | $110.40 * 2767 $305476.8 | 38-Game Ticket | $6 | 56% | $3.36 * 38 = $127.68 | $127.68 * 1107 = $141341.76 | Total Ticket Revenue | | | | 768 657.76 | Concessions Expected amount to spend on concessions = 0.08 * 0 + 0.11 * 2.5 + 0.45 * 8 + 0.36 * 13 = 8.56 (Numbers per category are derived by taking the average between the range, e.g. between $6 and $10 is 8.) Concession Revenue assuming each person spends $8.56 per game they attend | One Game Purchaser | 5-Game Purchaser | 20-Game Purchaser | 38-Game Purchaser | Total | Number of people interested in purchasing | 11621 | 6087 | 2767 | 1107 | | Number that will actually purchase | 80% * 11621 = 9296.79 | 94% * 6087 = 5721.78 | 92% * 2767= 2545.64 | 56% * 1107 = 619.92 | | Number of games each individual will attend | 100% * 1 = 1 | 97% * 5 = 4.85 | 95% * 20 = 19 | 90% * 38 = 34.2 | | Total Concession Revenue | 79580.52 | 237 545.42 | 414022.89 | 181482.82 | 912631.65 | Total Concession Profit | | | | | 39% * 912631.65 = 355926.34 |

Donations Financial support received from the City of Springfield and 3 nearby colleges = $21 000 Funds received from local businesses for sponsorships and advertising = $25 000 Fixed Expenses Players’ Salaries | $887 000 (Subsidized) | Bats and Balls | $22 500 (Subsidized) | Uniforms | $8 000 | League Dues | $175 000 | Staff Salaries | $124 000 | Office Expenses | $110 000 | Team Travel | $455 000 | Market research & mailing lists | $4 879 | Advertising, sales and marketing | $175 000 | Total Fixed Expenses | $1 961376 | Total Fixed Expenses Less Subsidies | $1051879 |

Projected Profit Add: Ticket Revenue = $768657.76 Add: Concession Profit = $355926.34 Add: Donations = $46 000 Less: Fixed Expenses = $1051879 Net Profit = $118705.10