Springfield Nor'Easters Case Analysis

Kevin Tame Business Research

2/23/2010

Springfield Nor’easters Case #1 Evaluate the research survey undertaken by the League Sports Association and by Larry Buckingham, Nor’easters marketing director. Consider each step in the process that led to the findings of the survey

Buckingham started his research by using the League Sports Association survey done in 2005 and confirmed that families with school age children were more likely to attend sporting events. He also found that 73% of the audience of baseball games had an income ranging from $22,500 to $75,000. This information was useful however Buckingham had done this only to confirm some of the anecdotal findings listed in the local newspaper. He knew that just a newspaper article and a three year old survey that covered four different major to minor league sports was not sufficient to make any decisions. He then decided that going forth with a market research survey was key in making any proper business decisions. Buckingham’s first steps in developing a market research survey was to decide how to answer the questions of how many people will come to Nor’easters games and how much shall tickets cost? He started by calling a number of marketing directors of minor league teams in order to help him better understand their business and their marketing perspectives. Most of directors had similar ideas and he decided that with this little bit of guidance he could set out to design a survey. He knew that done correctly he would maximize information yield for management decisions and help to shed light on the trade-offs between ticket pricing and concession sales. Realizing that a mail only survey would take too much time and money, Buckingham opted to mail out post cards that would direct participants to a web site. This method would reduce his cost and waiting time for the results. Before releasing the study to the public Buckingham conduct a few pretest to see if questions were confusing and needed to be revised or omitted. He found that some needed questions needed revision so he changed them for the better. After doing the initial investigation and pretest, Buckingham issued the survey to 10,000 individuals in Springfield and offered the chance to win a reward of $500 worth of restaurant gift certificates. He designed the questions of the survey based on what he had learned from the marketing director and the research he had done using the League Sports Association survey. Since Buckingham wanted his survey to answer the two questions of price sensitivity and sports attendance patterns, three sections focusing on seat location, concessions, and personal background were created. Participants would answer these questions from each category and Buckingham would then be provided with the information necessary to create proper pricing. Buckingham believed that the people that received the survey represented a decent sample of Springfield’s population. In the end, there was 625 people who responded and he was happy with those number even though they were weighted somewhat to people with children. Buckingham knew this represented the target market and was not concerned with the large amount of people with children represented in the sample. The overall results of the survey provided Buckingham with enough insight to be able to make a decent decision on ticket pricing and overall perspective of the target audience.

#2 What do you consider to be the key findings of the research survey? Comment on what Buckingham learned about a prospective customer profile, pricing, and single-ticket versus seasonticket packages

There are a number of key findings that Buckingham can take away from the survey. First, he now has a profile of potential customers. The customer profile is people who are 26-35 years of age with children, have an income between $22,500 to $75,000, would attend under 5 games per year or two, not necessarily a baseball fan, and are looking for family entertainment. This profile can then be used to understand who is coming to games and why they are coming. It is also assumed that of the customer profile about 391 percent of the population would be willing to go to at least 1 game a year. This means the Buckingham can assume that 21,582 people will at least come once in the season. Another take away is that Buckingham has a good idea of what customers are willing to pay for a ticket. Most customers are not willing to pay more for premium seating and are willing to pay between $10-$14 per game. The market for single ticket buying is the biggest and it is assumed that attendees are attending in substitution of other entertainment options and pricing has to be set as such. There is only a small amount of market for the full season tickets and lowering the price of tickets will be necessary to increase demand. However, concession will make up for the lowering of the ticket price. #3 What considerations should the Nor’easters take into account in establishing a pricing policy?

The few consideration that need to be addressed in establishing a pricing policy are tickets and concessions revenue at each price point, attendance at each price point, and the discounts offered amongst different price points. As addressed in the next previous question assumptions of how many people will eventually go to each game is key to establishing a price. However, if no one goes at all there is no reasonable price that can compensate for lack of attendance. Competing with other forms of entertainment such as movies and bowling is also important to consider. #4 Design a ticket pricing plan for the Nor’easters first season. Be very specific, and explain the assumptions, especially assumptions of cause and effect, that underlie your strategy. Should Buckingham offer more than one type of season package? How, if at all, should ticket pricing vary by package type? How, if at all, can Buckingham take advantage of consumer interest in grandstand seating?

The ticket pricing plan is mostly derived from the survey. There are some reasonable assumption that can be made by analyzing the data received, however there are some limitations to what is found. First, grandstand seating is not important to the populations and the survey shows 72%2 will not pay more than 10% of the original ticket price. Since they are dealing with such low ticket prices Buckingham can assume that selling a higher general admission ticket to everyone is better than discounting for non premium seats. Make it a first come first serve biases. The packaging type and concession sales is very important to the price decision making strategy (See Figure 1). The price people would be willing to pay for just 1 ticket or full season package depends on the price and discount given to multiple ticket purchasers. For example, at the single game price Buckingham can sell tickets at $14 but he is only going to get 14% of the people willing to go. This means there will be less attending and less to buy concession. However, if he decides to sell tickets at $10 there would be 80% attendance. According to Figure

1 the optimal pricing where concession and ticket sales are producing the greatest amount of revenue is $10. If Buckingham goes below that price the revenue generated begins to decrease. It is also important to note that as concessions spending goes up the amount of people spending goes down. 81%3 of the people are willing to spend between $6-$10 on concessions so it is assumed that $8 is typical of what 81% of the people will spend. Since concession and ticket prices are used as variables to calculate the optimal pricing mix for a single ticket the same design can be used on all reaming packaging option. The results were as follows and can be see in Figure 1: • Single Ticket Option - $10 and individuals buying $8 worth of concession • 5 Game Ticket Option - $8 and individuals buying $8 worth of concession • Half-Season Ticket Option - $6 and individuals buying $8 worth of concession • Full-Season Ticket Option - $4 and individuals buying $8 worth of concession #5 Using the pricing plan you have designed and given Buckingham’s assumptions about concession sales, will the team reach breakeven in the first year? If not, what options does Buckingham have to reach his target?

At the current product prices Buckingham can expect to have a profit of $53,676 (See Figure 2). To calculate this profit Buckingham would first need to figure out the total population of Springfield that would be willing to go to at least one game during the year, which is 21,5824. Next, he must assume that amongst the population 54%5 would be interested in going to one game, 28% would be interested in at least 5, 13% would be interested in half the season, and 5% would be interested in attending the full season. Now of that 54% who would be interested to go to one game, 80% 6 of them would actually go at $10. With the same rules applied to the other pricing packages, 9297 people would go to one game, 5722 people would go to 5 games, 2546 people would go to 20 games, and 908 would go to the full season (Figure 2). From that it is then possible to calculate that $765,258 of revenue would be generated from ticket sales for the entire season. Ticket sales is not the only revenue generator that depends on customers. Concession can make up another 30%-50% of revenue on top of ticket sales. Buckingham assumes that not every one will buy concession, especially people who buy a ticket and do not show. To calculate how much will be generated by concessions three variables need to be considered. One, the percentage of people not showing up to a game. Two, the percentage of people who will buy concessions at a certain price. Three, the profit margin that is generated from concession. For example, at the 5 game pricing mix a person is going to have a 97% chance of showing up and is going to have a 81% chance of buying at least $6-$10 in concessions. Once that number is calculated with the number of games the individual is attending and the number of people in the category, the final number will then need to be multiplied by 39% to give you a total of $70,1337. The same calculation can determine the hypothetical amount concessions will bring by each group. This total amount is approximately $294,297 generated from concessions for each pricing package. Adding the concession, ticket sales, support from town and school, and sponsorship from local businesses there is a total of $1,105,555. The fixed cost is given as $1,051,879 so subtracting that from $1,105,555 gives a net profit of $53,676. Buckingham is going to make a profit but only if people attend games. There is always the chance that no one will show up. However, according to the data the survey uncovered it appears that there will not be any problems.

Figure 1 Single Game

Single Game Optimal Pricing $ on concessions spent per game $! % who buy concessions % who show up # of games People interested in going Price People who would actually go Revenue from Tickets

4 $! 81%

8 $! 81%

$120,000

13 36%

$90,000

$!

100% 1 11621 14 $! 22% 35,793 $!

12 $! 49% 68,331 $!

10 $! 80% 92,968 $!

8 $! 93% 86,460 $!

6 $! 98% 68,331 $!

4 100% 46,484

Revenue from Concess @ $4 Revenue from Concess @ $8 Revenue from Concess @ $13

$! $! $!

3,231 $! 6,461 $! 4,666 $!

7,195 $! 14,391 $! 10,393 $!

11,747 $! 23,495 $! 16,968 $!

13,656 $! 27,313 $! 19,726 $!

14,391 $! 28,781 $! 20,786 $!

14,684 29,369 21,211

Total Revenues @ $4 Con Total Revenues @ $8 Con Total Revenues @ $13 Con

$! $! $!

39,023 $! 42,254 $! 40,459 $!

75,527 $! 82,722 $! 78,725 $!

104,715 $! 116,463 $! 109,936 $!

100,116 $! 113,773 $! 106,186 $!

82,722 $! 97,113 $! 89,118 $!

61,168 75,852 67,695

$!

$60,000

$30,000

$0 $14

$12

% who show up # of games People interested in going Price per ticket People who would actually go Revenue from Tickets

4 $! 81%

8 $! 81%

$225,000

$!

10 $! 75% 228,269 $!

8 $! 94% 228,878 $!

6 $! 97% 177,137 $!

4 99% 120,526

Revenue from Concess @ $4 Revenue from Concess @ $8 Revenue from Concess @ $13

$! $! $!

1,865 $! 3,731 $! 2,694 $!

14,549 $! 29,098 $! 21,015 $!

27,979 $! 55,958 $! 40,414 $!

35,067 $! 70,133 $! 50,652 $!

36,186 $! 72,372 $! 52,269 $!

36,932 73,864 53,346

Total Revenues @ $4 Con Total Revenues @ $8 Con Total Revenues @ $13 Con

$! $! $!

23,170 $! 25,036 $! 23,999 $!

156,989 $! 171,538 $! 163,455 $!

256,248 $! 284,227 $! 268,683 $!

263,945 $! 299,011 $! 279,530 $!

213,323 $! 249,509 $! 229,405 $!

157,458 194,390 173,872

$150,000

$75,000

$0 $14

$12

% who show up # of games People interested in going Price People who would actually go Revenue from Tickets Concessions revenue @ $4 Concessions revenue @ $8 Concessions revenue @ $18

8 $! 81%

$8

$6

$4

Total Revenues @ $4 Con Total Revenues @ $8 Con Total Revenues @ $13 Con Half-Season $500,000

13 36%

$375,000

$!

95% 20 2767 14 $! 1% 7,747 $!

12 $! 16% 106,249 $!

10 $! 51% 282,224 $!

8 $! 69% 305,466 $!

6 $! 92% 305,466 $!

4 99% 219,138

$! $! $!

664 $! 1,329 $! 960 $!

10,629 $! 21,257 $! 15,352 $!

33,879 $! 67,757 $! 48,936 $!

45,836 $! 91,672 $! 66,207 $!

61,115 $! 122,229 $! 88,277 $!

65,765 131,529 94,993

$!

$10

Ticket Price

Half-Season Optimal Pricing 4 $! 81%

$4

$300,000

12 $! 39% 142,440 $!

$ on concessions spent per game $! % who buy concessions

$6

5 Games

13 36%

97% 5 6087 14 $! 5% 21,305 $!

$!

$8

Total Revenues @ $4 Con Total Revenues @ $8 Con Total Revenues @ $13 Con

5 Game Optimal Pricing $ on concessions spent per game $! % who buy concessions

$10

Ticket Price

$250,000

$125,000

$0 $14

$12

$10

$8

$6

$4

Ticket Price Total Revenues @ $4 Con Total Revenues @ $8 Con Total Revenues @ $13 Con

$! $! $!

8,412 $! 9,076 $! 8,707 $!

116,878 $! 127,506 $! 121,601 $!

316,103 $! 349,981 $! 331,160 $!

351,302 $! 397,138 $! 371,673 $!

366,580 $! 427,695 $! 393,742 $!

284,903 350,668 314,132

Total Revenues @ $4 Con Total Revenues @ $8 Con Total Revenues @ $13 Con Full-Season

Full-Season Optimal Pricing $ on concessions spent per game $! % who buy concessions % who show up # of games People interested in going Price People who would actually go Revenue from Tickets Revenue from Concess @ $4 Revenue from Concess @ $8 Revenue from Concess @ $13

4 $! 81%

8 $! 81%

$300,000

13 36%

$225,000

$!

90% 38 1107 14 $! 1% 5,888 $!

12 $! 11% 55,515 $!

10 $! 22% 92,525 $!

8 $! 36% 121,124 $!

6 $! 56% 141,311 $!

4 82% 137,947

$! $! $!

478 $! 957 $! 691 $!

5,261 $! 10,522 $! 7,599 $!

10,522 $! 21,045 $! 15,199 $!

17,218 $! 34,437 $! 24,871 $!

26,784 $! 53,568 $! 38,688 $!

39,220 78,439 56,651

$!

$150,000

$75,000

$0 $14

$12

$10

$8

$6

Ticket Price Total Revenues @ $4 Con Total Revenues @ $8 Con Total Revenues @ $13 Con

$! $! $!

6,366 $! 6,845 $! 6,579 $!

60,776 $! 66,037 $! 63,115 $!

103,047 $! 113,570 $! 107,724 $!

138,342 $! 155,561 $! 145,995 $!

168,095 $! 194,879 $! 179,999 $!

177,166 216,386 194,597

Total Revenues @ $4 Con Total Revenues @ $8 Con Total Revenues @ $13 Con

$4

Figure 2 Inputs Single game price 5 game package (price per game) 20 game package (price per game) Season 38 games (price per game) Concessions (expected amount for individual to spend) Maximum capacity of stadium Average amount of seats filled % of Attendance

$! $! $! $! $!

10 8 6 4 8 3600 3245 90%

Attendance of town Population of town Yearly Attendance

39% 55,338 !21,582

Fixed expenses Uniforms League dues Staff salaries Office expenses Team travel Market research & mailing lists Advertising, sales and marketing

$! $! $! $! $! $! $!

Total Fixed Expenses

$!1,051,879

8,000 175,000 124,000 110,000 455,000 4,879 175,000

Profit Analysis One Game 5 Game Half Season Full Season Percentage of people who would be interested 54% 28% 13% 5% Number of people that would go at least once a year 11621 6087 2767 1107 Percentage of people who would actually go 80% 94% 92% 82% Number of people that would actually go 9297 5722 2546 908 Number of games attended 1 5 20 38 245 753 1340 908 Avg attendance per game Revenue per person $! 10 $! 40 $! 120 $! 152 Total Revenue from ticket sales per year

$!

% of People who show up Concessions (% of people who will buy) Profit Margin Revenue from Concession per year

92,968 $!228,878 $! 100% 81% 39%

$!

97% 81% 39%

23,495 $! 70,133 $!

Total

305,466 $! 137,947 $! 765,258 95% 81% 39% 122,229 $!

90% 81% 39% 78,439 $! 294,297

Support from town and school Sponsorship from local businesses

$! $!

Total Streams on Incoming Funds

$!1,105,555

Fixed Expenses

$!1,051,879

Total Profit

$!

21,000 25,000

53,676

End Notes Derived from responses of how many games respondents would attend [2%(Full)+ 5%(Half)+11%(5)+21%(1)] Derived from respondents saying that they would only pay 10% more [24%(Not pay more) + 48%(Pay 10% more)] 3 Derived from respondents saying that they pay at least $6-$10 [45% ($6-$10) +36% ($11-$15) 4 39%(see footnote 1) of Population (55,338) 5 21% of the 39% is 54% 6 At $10 ticket price 80% [22% ($14)+ 27% ($12) + 31% ($10)] would be willing to pay. From question 8 of survey 7 5722(people) x 5(game) x 97%(show up) x 81%(concession buying %) x 39%(profit margin) x $8(average concession amount) 1 2