Nicole Afable
Professor Vermillion
MKT 202
3/3/15
Blanca’s Soup Cart
Recommendations
The results of the research for Blanca’s soup cart help to distinguish her company’s best
choices when it came to product, place, profit, price, and target market. First, it was important
to determine the most popular soups within the consumer population (held at least 25% of
customer votes)—Broccoli & Cheese, Beef Chili, Vegetable, Black Bean, Tortilla and Chicken
Noodle. Next, the place of the location amongst the DePaul Loop Campus offered a greater
profit of $190,200 a year in comparison to the competing location of Wicker Park bringing in
only $89,325. The chosen price of using the optimal price point of $4.25 per unit of soup meets
the range of acceptable prices. Although a higher pricing of soup at $5.25 per unit would bring
forth a faster breakeven point, more customer would be willing to purchase from Blanca at a
price that is lower. The most effective target markets to advertise Blanca’s soup business
would be the racial group of African Americans since they hold the highest frequency of soup
consumption (35). Lastly, if Blanca were to add an additional product to her company, the best
lunch choice would be hot dogs, for they have the most similar correlation with soup likeability.
Product Strategy
Blanca needs to determine whether opening a soup cart in front of the DePaul Loop
Campus, or staying in school to pursue a career at $32,000 a year will be a more successful
choice. The first step is to determine which soups should be sold if a soup cart were to open
up. In order to do this, 133 students were told to write down their top five favorite soups on a
piece of paper. The data was then collected and organized in an Excel document. For every
soup that a respondent wrote down, a number “1” was used to record a point for that
particular soup choice.
Using this point system, the total of each soup type was then added up by taking the
sum of the points. The top five most popular soups could then be determined by these sums.
The results of these top five soups included Broccoli & Cheese (113 votes), Beef Chili (69 votes),
Vegetable (63 votes), Black Bean (62 votes), and Southwest Tortilla soup (55 votes). These top
five soups are now the evoked set.
To further display the results of the 133 respondents and their soup choices, the
response frequency had to be calculated. In order to do this, the total votes of each individual
soup were divided by the number of respondents (133). The percentages or response
frequencies of the soups were presented in a bar chart from the most popular to least popular
soup. A line was drawn to show the cutoff point of 25% or more of the students. The evoked
set would be more easily distinguished by over passing that cutoff point. This is because the
soups of Broccoli & Cheese, Beef Chili, Vegetable, Black Bean, and Southwest Tortilla hold the
following response percentages: 85%, 52%, 47%, 47%, 41%.
From the results of finding the evoked set from the soup, Blanca can now determine the
most profitable soups for her business based on these 133 respondents. Broccoli and Cheese,
Beef Chili, Vegetable, Black Bean, and Southwest Tortilla soup held at least 25% of the response
frequency as well as the greatest number of votes from the individuals when compared to all of
the other soup choices. Using these top 5 soups would be the best recommendation of which
to sell since they hold a majority of the votes from the respondents.
Demand Estimation
To further the research regarding demand, a survey of 166 individuals who were found
at the DePaul Loop Campus was collected asking the following information regarding lunch:
their preference of eating soup, a deli sandwich, burrito, hamburger, pizza, or hot dog from 1-6
(1 being their least preferred), the frequency in which they eat soup (never, once a year, twice a
year, once a month, twice a month, once a week, or two or more times a week), their
considered price for soup that is considered expensive, cheap, beyond expensive, and beyond
cheap, their number one preference out of the evoked set of soups (Broccoli and Cheese, Beef
Chili, Vegetable, Black Bean, or Southwest Tortilla), their gender (female or male), their race
(Hispanic / African American), White, or other), and how much they agree with eating out for
lunch (Strongly agree, somewhat agree, neither agree or disagree, somewhat disagree, or
strongly disagree).
The data collected regarding all 166 respondents and their eating frequency of soup was
focused on first. The response of each individual was consolidated to find the response
frequency of each of the responses (never, once a year, twice a year, once a month, twice a
month, once a week, or two or more times a week). To do this, an encoding was used to sum
up the number individuals who chose each response choice. The response frequency
concluded the results of 72 respondents eating soup two or more times a week, 140
respondents eating once a week, 136 respondents eating twice a month, 105 respondents
eating once a month, 60 respondents eating twice a year, 41 respondents eating once a year,
and 62 respondents never eating soup. To calculate the response frequency percentage, each
number was divided by the total of respondents to get the following: 12%, 23%, 22%, 17%,
10%, 7%, and 10%. The types of responses and their response frequency were displayed in a
column chart. This showed that a majority of individuals eat soup once a week and the least
amount of the respondents eat soup once a year.
The next step was to calculate the category incidence frequency per year and per day.
By obtaining this information, an estimate of units sold upon a chosen location can be
determined. The interpretation per year was given a value of 104 for two or more times a
week, 52 for once a week, 24 for twice a month, 12 for once a month, 2 for twice a year, 1 for
once a year, and 0 for never. For example, the value of 12 was given to the response of ‘once a
month’ considering there are 12 months in a year (meaning that individual ate soup at least one
time per month in a given year). Using the same concept, the interpretation of soup eating
frequency per day was calculated to have a value of .29 for two or more times a week, .14 for
once a week, .07 for twice a month, .03 for once a month, .01 for twice a year, .003 for once a
year, and 0 for never.
By taking the response frequency for each given response, and the interpretation per
year, the category incidence frequency can be calculated. The product of the response
frequency and the interpretation must first be computed and then the sum of the answers for
each response will give you the CIF. The CIF was totaled to 32 per year. Using the same
response frequency but replacing it with interpretation per day, yields a CIF of .09 per day.
Next, we had to compare the units of soup sold depending on the location of Blanca’s
soup cart. The first location would be open for 4 days a week with an average of 5000 people
at DePaul Loop Campus. The alternate location would be held at Wicker Park and open for 6
days. To find the number of sales per day, the CIF per day had to be multiplied by the number
of people that would be at the specific location. For DePaul the sales per day would be 450.
Wicker Park would yield about 113 sales per day. Taking the sales per day times the days per
week that each location would be open for, will total to the weekly sales for the soup cart. This
would conclude for having weekly sales of 1,800 (4 days X 450 sales per day), monthly sales,
7,800, and yearly sales of 93,600. For Wicker Park the weekly sales would be 675, monthly
sales of 2,925, and yearly sales of 35,100.
The same process was used to calculate the CIF per year based upon gender and upon
race. For females, the CIF held a value of 14.69 and males of 16.89. When the gender
frequencies were displayed side-by-side on a graph, most males responded of eating soup once
a week (13% of the 616 respondents) and the least amount of them responded to eating soup
once a year (3%). For females, the most responses were for eating soup twice a month (10.4%)
and the least amount of them responded to eating soup once a year (4%). Based upon race,
the CIF per year were 29.98 for Hispanics, 35 for Black/African Americans, 31.5 for Whites, and
32.4 for other. With the data shown in a column chart, Hispanics held the highest response
frequency for each response choice but the least likely to buy soup from the CIF value of 29.98.
Interpreting all of this information I would recommend opening up a soup cart in Wicker
Park for 6 days a week would be the more profitable choice—bringing a greater amount of sales
per year (35,100) versus opening up one on the DePaul Campus (9,600). Referring back to the
previous calculations, the prediction of males being more likely to purchase soup is greater than
females. As of race, the results predict that Hispanics will be the least likely to purchase soup
from the soup cart (CIF of 29.98) and Black/African Americans most likely to purchase soup (CIF
of 35).
Price Strategy
The focus here is to identify a reasonable price for the product using the Price Sensitivity
Method. The responses from the 166 respondents and the prices that they consider a unit of
soup to be cheap, expensive, cheap beyond consideration, and expensive beyond consideration
were used. For each of these categories, intervals of $0.25 were used to organize all the data.
These intervals started from a value of $0.00 to $9.99. The frequency for each range was
calculated to see how many people responded with a price between the given values.
Displaying this organized data into a four frequency distribution chart helped to display the
Indifference Price Point, Point of Marginal Cheapness, Point of Marginal Expensiveness, and
Optimal Price Point.
The Indifference Price Point is the point where equal number of respondents believe the
test product is expensive as believe it is inexpensive. This usually reflects either the median
price that consumers actually already pay in the market or the market leader’s price of the
product. This value, collected from the 166 respondents equaled $4.25.
The Point of Marginal Cheapness is the point where an equal number of the
respondents believe the product is expensive as believe it is too inexpensive. From the
collected data, the PMC held a value of $3.25. The Point of Marginal Expensive is where an
equal number of respondents believe the product is too expensive as it is inexpensive. The
value of PME for soup prices equaled $5.25. The values that fall between the range of PMC and
PME ($3.00 - $5.25) are seen as acceptable prices for each unit of soup.
Lastly, the Optimal Price Point indicates where the same number of respondents believe
the price is too expensive as it is too inexpensive. This value can be seen as the ideal price point
for each unit of soup at Blanca’s soup cart. The OPP given from the collected data equaled
$4.25.
Given these values of the IPP, PMC, PME, and OPP, a recommendation would be for
Blanca to use the price of $4.25. With this price being within the range of acceptable prices, as
well as the value of the Optimal Price Point, it seems best to use this value to price Blanca’s
soups. Using $4.25 per unit of soup, it would be able to bring in more profit than that of the
lower PMC value. Also, because the price is around the middle value of the acceptable price
range, the value would be just enough to make profit and not too risky to lose profit by using
the PME.
Distribution Strategy
Distribution strategy helps to focus on the profit and loss of Blanca’s soup cart company
at the previously calculated price points of the IPP, PME, PMC, and OPP. We are given the
information that the variable cost would be $1.50 per unit (covering food, cooking, and
presentation). The fixed costs, however, would vary depending upon the location—DePaul
Campus or Wicker Park. Both places would need to pay a monthly fee for the cart rental
($250), food server’s license ($100), and other utilities ($250). DePaul would have to pay an
additional $5,000 a month to rent on campus for a food vendor. This would total Wicker Park’s
fixed costs per month to $600 and DePaul’s fixed costs to $5,600.
The breakeven point helps to determine the number of units in which profit equals costs
which is neither profit nor loss. By using the different price points and placing them into the
breakeven formula (FC / (Price – VC)) the breakeven values were found for both locations. With
these values displayed on a line graph, the greater the price was for each unit of soup, the
sooner the breakeven point was able to be reached. For example, the PME Price of $5.25
would reach breakeven at 1,493 units on the DePaul Campus. On the other hand, at the same
location, the PMC price of $3.25 would reach the breakeven point at 3,200 units.
A forecast of the profit for each location further helped to see where the soup cart
would be more successful. By using the previously calculated units sold, the profit equation
(Profit = Quantity * (Price – Variable Cost) – Fixed Cost) would give us the respected monthly
profit. For the DePaul location which would be open for 4 days a week with 5000 people
passing through, an estimated monthly profit of $15,850 and a yearly profit of $190,200 would
be made. For the Wicker Park location that would be open for 6 days a week with 1,250 people
passing through, an estimated monthly profit of $7,443.75 and a yearly profit of $89,325 would
be made.
Considering these profit forecasts as well as the option for Blanca to work a $32,000 a
year career, the most successful choice would be for her to open up a soup cart at the DePaul
Loop location. This would bring her a profit of about $190,200 a year which is the best out of
her three options. The perks of using this location is not only greater profit. Blanca would also
be able to only have a work week of 4 days which is much less than the Wicker Park location. In
the least amount of time, she would be able to reach a greater community of people (5,000).
Although the price point of $4.25 would not reach a faster breakeven point as if it were priced
at $5.25, the profit gained from her soup cart will still be quite high.
Target Market Selection
It is important to know which market to target a specific product to. With the Blanca’s
product being soup, the 166 surveys can be utilized to determine her target market. Gathered
data of the 166 respondents regarding gender and race were investigated first. To do this, each
category of gender (male or female) or race (Hispanic, African American, White, or Other) must
be organized regarding their eating frequency of soup. The previously calculated CIF males held
a value of 16.89 while females held a value of 14.69. Interpreting this information shows that
males have only a slightly more frequent preference of eating soup than females do. To further
this evaluation, a P-value t-test was taken. The P-value of the gender data (.857) was greater
than the chosen alpha of 5%. This means that we are to accept the null hypothesis and that
the data is due to random sample error. This proves that both males and females are from the
same population while their difference is statistically insignificant. Summing all of this
information up shows that difference in gender does not affect one’s frequency in consumption
of soup.
To determine whether race has any affect on the frequency of soup consumption, an ftest was taken. The single factor f-test summary gave a p-value of .0001 for between groups.
In comparison to the chosen alpha of 5%, the p-value was a less than the chosen alpha.
Because of the lesser value, we are to reject the null hypothesis. In addition, the samples can
be seen as statistically significant. In other words, the frequency of eating soup is dependent
upon the race of the customer. The results showed that a customer of Hispanic background
yields an average frequency of about 45.43, while that of African American background yields
an average of 18. If the customer is of white background, their average in eating frequency is
10.71 while a customer of other race yields a frequency of 13.86. Although Hispanics have a
greater average in frequency, the CIF values of each racial group say something different.
Hispanics hold a CIF of 29.98. African Americans hold a CIF of 35. Whites hold a CIF of 31.53
and other racial groups hold a CIF of 32.41. The CIF value of Hispanics shows the lowest value
explaining that they eat soup less frequently than any of the other races. A bar graph including
races and their respected CIF values, show that the most frequent to least frequent soup
consumers are as follows: Black/African Americans, other racial groups, whites, and then
Hispanics.
The next set of research dove more in depth with gender investigation. The 166
respondents were placed into one of two groups. The first was called the ‘Top Two Boxers’
meaning they agreed or strongly agreed to the liking of eating out for lunch. The second
groups, known as the Brown Baggers, were all of the respondents who did not meet the criteria
for the first group. Males had a total of 210 Two boxers while females held a total of 203. As of
Brown Baggers, males held a total of 105 while females held a total of 98. This showed that the
difference in gender did not necessarily affect their preference of eating out for lunch. With a
p-value of .8379 for the chi test, it exceeded the chosen alpha of 5% deeming the data
statistically insignificant.
Lastly, a regression analysis was taken to analyze the preference of soup against other
lunch alternatives. The alternative choices for lunch were a deli style sandwich, burrito,
hamburger, pizza and a hot dog. The surveyed individuals were told to rank each of these
choices, along with soup, on a scale of preference from 1-6 (1 being the highest). The
frequency of lunch choice was organized by the scale of preference for all of the 166
respondents. The results were then plotted to determine their correlation with soup. The plots
showed that if someone were to like soup, they would also probably like hot dogs for lunch. On
the other hand, if an individual were to eat soup, they would probably dislike the choice of a
hamburger for lunch.
Consolidating all of the gathered information regarding target market and
segmentation, race would be a more effective market to aim at. African Americans held the
greatest CIF value (35) showing they are most frequent group to consume soup. Gender on the
other hand is not statistically significant. Therefore, the difference in gender does not affect
soup consumption. The regression analysis displayed that those who prefer soup also may
prefer hot dogs. In contrast, those who prefer soup may not find likeability toward eating
hamburgers for lunch. If Blanca were to expand her food selection and sell another lunch item
within her food cart, hot dogs have the most similar correlation to soup. Therefore, this would
be the smartest choice.
APPENDIX
Product
What Soups Should She Sell?
Kind of Soup
Broccoli & Cheese
Chili (Beef)
Vegetable
Black Bean
Tortilla (Southwest)
Chicken Noodle
French Onion
Egg Drop
Clam Chowder
Lobster Bisque
Beef w/ Vegetable
Chicken and Rice
Mushroom
Chili Turkey
Split Pea
Matzo
Miso
Lentil
Cream of Chicken
Cream of Broccoli
Corn Chowder
Chicken and Dumplings
Beef Barley
Squash
Italian Wedding
Thai
Potato
Lemon Drop
Chinese
Seafood
Pho
Manhattan Clam Chowder
Kimchi & Ramen
Creamy Mushroom
Cream of Crab
Cioppino
Borsch
Beer Cheese
Beef Noodle
5 Bean
0.0%
20.0%
40.0%
60.0%
Frequency(%)
80.0%
100.0%
Category Incidence Frequency Table
Percentage
Overall DePaul Soup Eating Frequency
25%
20%
15%
10%
5%
0%
Two or
More times
a Week
Once a
Week
Twice a
Month
Once a
Month
Twice a
Year
Once a Year
Never
Response Frequency
Percentage
Soup Response Frequency by Gender
14%
12%
10%
8%
6%
4%
2%
0%
Male Frequency
Female Frequency
Two or
More
times a
Week
Once a Twice a Once a Twice a Once a
Week Month Month
Year
Year
Never
Response Frequency
Percentage
Soup Response Frequency by Race
14.0%
12.0%
10.0%
8.0%
6.0%
4.0%
2.0%
0.0%
Hispanics
Black / AA
Two or Once a Twice a Once a Twice a Once a
More Week Month Month Year
Year
times a
Week
Response Frequency
Never
Whites
Other Races
Category Incidence Frequencies
Eating Frequency
Per Day
Per Year
0.09
32
Gender Frequency
Male
Female
16.89
14.69
Race Frequency
Hispanic
Black/AA
White
Other
29.38
35
31.53
32.41
Demand Estimation Table
Location
DePaul
Wicker Park
People
5000
1250
Days /
Week
4
6
Sales / Day
450
112.5
Weekly
1800
675
Monthly
7800
2925
Yearly
9600
35100
Price Estimation Table and Graphs
Price Sensitivity Meter
120%
100%
80%
60%
Considered Expensive
Considered Cheap
40%
Expensive beyond
consideration
20%
Cheap beyond
consideration
0%
Detailed Sensitivity Meter
25%
IPP
20%
15%
Considered Expensive
PMC
10%
5%
Considered Cheap
PME
Expensive beyond
consideration
OPP
Cheap beyond
consideration
0%
Price Perception
PMC
IPP
OPP
PME
Use For Class
$3.25
$4.25
$4.25
$5.25
From Chart Above
$3.10
$4.10
$3.95
$5.25
Profit / Loss Analysis by Location
$34,000.00
$32,000.00
$30,000.00
$28,000.00
$26,000.00
$24,000.00
$22,000.00
$20,000.00
$18,000.00
$16,000.00
$14,000.00
$12,000.00
$10,000.00
$8,000.00
$6,000.00
$4,000.00
$2,000.00
$0.00
-$2,000.00
-$4,000.00
-$6,000.00
-$8,000.00
IPP
OPP
PME
PMC
0
400
800
1200
1600
2000
2400
2800
3200
3600
4000
4400
4800
5200
5600
6000
6400
6800
7200
7600
8000
8400
8800
9200
9600
10000
Profit
DePaul Profit & Loss
Volume
$34,000.00
$32,000.00
$30,000.00
$28,000.00
$26,000.00
$24,000.00
$22,000.00
$20,000.00
$18,000.00
$16,000.00
$14,000.00
$12,000.00
$10,000.00
$8,000.00
$6,000.00
$4,000.00
$2,000.00
$0.00
-$2,000.00
-$4,000.00
-$6,000.00
-$8,000.00
IPP
OPP
PME
PMC
0
400
800
1200
1600
2000
2400
2800
3200
3600
4000
4400
4800
5200
5600
6000
6400
6800
7200
7600
8000
8400
8800
9200
9600
10000
Profit
Wicker Park Profit & Loss
Volume
Break Even Volume
Price Point
IPP
OPP
PME
PMC
Monthly
Yearly
DePaul Campus
2036
1493
3200
2036
DePaul Expected Profit
$15,850.00
$190,200.00
DePaul Campus
Wicker Park
Chosen Price
Variable Cost /
Unit
$4.25
$4.25
$1.50
$1.50
Fixed Cost
Expected Sales
Volume / Day
Expected
Monthly Profit
Expected
Annual Profit
$5,600.00
$600.00
450
112.5
$15,850
$7,443.75
$190,200.00
$89,325.00
Market Segmentation
T-Test for Gender on Eating Frequency
Wicker Park
218
160
343
218
P-value
Male
0.8567
Female
0.8567
Averages
45
43
44
44
Statistically
Insignificant
Statistically
Insignificant
16.89
14.69
Overall
Average
Interpretation
of Statistical
Relevance
CIF
Anova: Single
Factor
SUMMARY
Groups
Hispanic
Frequency
Black / AA
Frequency
White
Frequency
Other
Frequency
ANOVA
Source of
Variation
Between
Groups
Within
Groups
Total
Count
Sum
Average
Variance
7
318
45.43
472.29
7
126
18.00
138.00
7
75
10.71
17.57
7
97
13.86
29.81
SS
df
MS
F
P-value
F crit
5310
3
1770
10.76533198
0.000113066
3.00878657
3946
24
164.4166667
9256
27
Category Incidence Frequency
Category Incidence Frequency for Race
36.00
35.00
34.00
33.00
32.00
31.00
30.00
29.00
28.00
27.00
Hispanic
Black / AA
White
Other
Race
Axis Title
Liklihood of Gender Affecting Preference of Eating
Out
Brown Baggers
Male
Two Boxers
Famale
0%
20%
40%
60%
Axis Title
Chi-Squared Test Results
P-Value
0.8379
Alpha
0.05
Accept Null Hypothesis
Samples from same population
Statistically insignificant
80%
100%
Is the Preference of Soup Affected by Preference
of Deli Sandwiches for Lunch?
19
Frequency
14
9
Soup
Deli Sandwich
4
-1
0
1
2
3
4
5
6
Ranking of Preference (1-6)
Frequency
Is the Preference of Soup Affected by Preference
of Hamburgers for Lunch?
18
16
14
12
10
8
6
4
2
0
Soup
Hamburger
0
1
2
3
4
5
6
Ranking of Preference (1-6)
Is the Preference Soup Affected by Preference of
Burritos for Lunch?
Frequency
20
15
10
Soup
5
Burrito
0
0
1
2
3
4
Ranking of Preference (1-6)
5
6
Frequency
Is the Preference of Soup Affected by Preference
of Pizza for Lunch?
16
14
12
10
8
6
4
2
0
Soup
Pizza
0
1
2
3
4
5
6
Ranking of Preference (1-6)
Frequency
Is the Preference of Soup Affected by Preference
of Hot Dogs for Lunch?
18
16
14
12
10
8
6
4
2
0
Soup
Hot Dog
0
1
2
3
4
Ranking of Preference (1-6)
5
6