MKTG 4250, Product Strategy
Sandwich shops maps (in class activity + Assignment 3)
Professor Jay Waddell
Fall 2012
We will do Part I of this exercise in class on September 25.
Part II is Assignment 3. It is due in hard copy in class on September 25. Please see the specific What To
Hand In instructions at the end of this handout. Assignment 3 is worth 3 points.
In Part II, you are given the output from a statistical procedure and asked to interpret it. The format of
the data and the output is very similar to the swimsuit example in the book, on pages 127-133. Please
hand in individual work for this assignment.
Part II looks very dense and data rich, but if you read carefully, you will see that you are given very
specific tasks to perform. Both of these tasks are interpretive. You do not have to do any calculations,
but you do have to think carefully about the output you are given.
Part I: Build a “determinant gap map” of the sandwich shops in Boulder.
This is an in-class exercise. You may work in a small group. Please do your work on a separate sheet of
paper (i.e., not on this handout).
Step 1: First make a list of 10-12 sandwich shops in Boulder. Please include the following shops:
 Deli Zone
 Half Fast Subs on the Hill
 Jimmy Johns
 Snarfs
 Subway
 Silvermine Subs
Step 2: Think about those shops on your list, and use your judgment to identify two aspects of sandwich
shops which are differentiating, important, and independent. Use those two aspects to label the axes of
the map.
Step 3: Place all of the shops on your list (including the ones listed above) onto the map, making
judgments about how each place rates on both aspects (i.e., both axes).
Step 4: Are there any noticeable gaps in your map? What is your interpretation of that?
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MKTG 4250, Product Strategy
Sandwich shops maps (in class activity + Assignment 3)
Professor Jay Waddell
Fall 2012
Part II: Build a perceptual gap map based on attribute ratings from a survey
In this part, you will build a perceptual map of the sandwich shops in Boulder, using the data and the
resultant analysis from a survey about attributes of sandwich shops. You do not need to do any
statistical analysis—you are given all the output you need. Your assignment is to understand the data
that was collected and interpret the output of the analysis. There are two tasks in this part. Task #1 is to
name the factors. Task #2 is to build a map. Be sure to do both of them.
Step 1: Read the survey that was used to collect data.
The following questions were asked about each of the six sandwich shops listed in Part I.
Please indicate how much you agree or disagree with each of the following statements.
1 = Strongly disagree 2 = Disagree 3 = Neutral 4 = Agree 5 = Strongly agree
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
This place has filling sandwiches.
This place is clean.
This place has good variety.
This place has healthy choices.
This place has tasty food.
This place has good value.
This place has low prices.
This place has good hours of operation.
This place has fresh ingredients.
This place has good delivery options.
This place has a convenient location.
This place has good service.
This place has coupons available.
This place has greasy food.
This place has good atmosphere.
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
1 … 2 … 3 …. 4 …. 5
Step 2: Examine the average scores on each question for each shop.
The average scores for each shop for each question are shown in the chart and table below:
Table 1: Average rating (on a 1-5 scale) on each attribute for each shop:
5.00
4.50
4.00
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00
Filling
Clean
Variety
Healthy
Choices
Tasty
Good
Value
Low
Prices
Hours
Fresh
Delizone
4.32
3.53
4.21
3.63
4.32
3.42
2.89
3.63
3.84
3.00
4.11
3.74
3.11
3.32
3.84
Half Fast
4.56
3.56
4.58
3.56
4.36
3.72
2.47
4.08
3.83
3.22
3.89
3.61
3.28
3.03
4.33
Jimmy Johns
3.42
3.79
3.29
3.71
3.88
3.38
3.08
4.42
3.71
3.88
4.17
3.83
3.42
2.29
3.58
Snarfs
3.74
2.58
3.74
3.47
4.11
3.37
2.89
3.42
3.58
3.21
3.53
3.53
2.95
2.95
3.05
Silvermine
3.55
3.58
3.27
3.18
3.45
3.45
3.18
4.27
3.15
4.18
3.52
3.45
3.79
2.61
2.76
Subway
3.67
3.64
3.46
4.31
3.44
3.54
3.54
3.59
3.38
1.49
3.74
3.28
3.72
1.87
2.62
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Delivery Location Service Coupons Greasy
Atmosph
ere
MKTG 4250, Product Strategy
Sandwich shops maps (in class activity + Assignment 3)
Professor Jay Waddell
Fall 2012
Step 3: Examine the output of the factor analysis and name the factors
Similar to the analysis in Crawford and Di Benedetto’s Chapter 6 in the book (pp. 127-133), a “factor
analysis” was performed on the data to see if there were common underlying themes to the fifteen
attributes. For example, one might expect that the scores on the “good value” and “low prices”
questions would be tightly linked (that is, highly correlated). We would expect these attributes to be
related in a factor related to cost.
Here is the first piece of output from the analysis that was done (I used SPSS and Excel). Similar to Figure
6.7 in the book, Table 2 shows the Factor Loading Matrix, that is, the correlation of the original set of
attributes to their underlying factors.
Table 2: Factor Loading Matrix (like Figure 6.7)
Factor 1
Filling
0.8413
Clean
0.0849
Variety
0.8349
Healthy Choices
0.3238
Tasty
0.8395
Good Value
0.5544
Low Prices
-0.1742
Hours
0.1695
Fresh
0.6543
Delivery
0.0460
Location
0.3172
Service
0.2955
Coupons
-0.0257
Greasy
0.1871
Atmosphere
0.6961
Factor 2
0.0375
0.4884
0.0673
-0.1047
0.1970
0.2112
0.0346
0.7703
0.1272
0.7518
0.4069
0.4686
0.4708
0.0515
0.3499
Factor 3
-0.0575
0.5900
-0.0233
0.6899
0.0141
0.0926
0.1070
0.0289
0.3465
-0.3164
0.2095
0.0744
0.1551
-0.7285
-0.1053
Factor 4
0.0336
-0.1016
-0.0249
0.2988
0.0255
0.5886
0.8789
0.1214
0.0329
-0.1035
0.0513
0.2542
0.4350
-0.0961
-0.2961
Task #1: Name the factors.
In this analysis, the output showed four factors, instead of only two factors as in the swimsuit example
in the book (fashion and comfort). To name the factors, circle the “biggest” number in each row. (I put
“biggest” in quotes because a high loading can be a high positive or negative correlation. So you really
need to circle the number with the biggest absolute value in each row.) If the two biggest numbers are
close, circle them both.
For example, the first attribute, (filling sandwiches) is loaded most highly on Factor 1, so circle the .8413.
And the second attribute (clean) is loaded most highly on Factor 3, so circle the .5900.
Look at your pattern of circles. Try to give names to the groups of attributes that have circles on the
same factor (= the same column). Fill in the names you come up with below. This is a challenging but
realistic example.
Factor 1 name: _______________________
Factor 2 name: _______________________
Factor 3 name: _______________________
Factor 4 name: _______________________
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MKTG 4250, Product Strategy
Sandwich shops maps (in class activity + Assignment 3)
Professor Jay Waddell
Fall 2012
Step 4: Use the rest of the factor analysis output to build a map of the market
Table 3 shows the Factor-Scores Coefficient Matrix, that is, the regression weights that relate the
attribute scales to the factor scores. This output is similar to Figure 6.8 in the book.
Table 3: Factor-Scores Coefficient Matrix (like Figure 6.8)
Factor 1 Factor 2 Factor 3
Filling
0.2672 -0.1168
-0.0900
Clean
-0.0825
0.2615
0.4182
Variety
0.2578 -0.0940
-0.0534
Healthy Choices
0.0887 -0.1340
0.3821
Tasty
0.2374 -0.0296
-0.0392
Good Value
0.1476 -0.0302
-0.0965
Low Prices
-0.0546 -0.0373
-0.1140
Hours
-0.0678
0.3767
-0.0136
Fresh
0.1720 -0.0373
0.1930
Delivery
-0.0896
0.4066
-0.1903
Location
0.0269
0.1647
0.1149
Service
0.0200
0.1815
-0.0200
Coupons
-0.0850
0.2167
0.0110
Greasy
0.0884
0.0046
-0.4800
Atmosphere
0.1689
0.1059
-0.0403
Factor 4
0.0451
-0.2496
-0.0074
0.0757
0.0081
0.3896
0.6015
0.0095
-0.0564
-0.0752
-0.0442
0.1253
0.2325
0.0907
-0.2129
To get the final factor scores (i.e., a score for each shop on each factor), I follow the procedure described
in the bottom of Figure 6.8, multiplying the average attribute scores for each shop from Table 1 by the
corresponding factor-score coefficient from Table 3, and adding up all the products.
Table 4: The final results of the analysis
Delizone
Half Fast
Jimmy Johns
Snarfs
Silvermine
Subway
Factor 1
4.649
4.861
3.724
4.157
3.349
3.761
Factor 2
4.090
4.341
5.068
3.747
4.985
3.415
Factor 3
0.226
0.233
0.804
-0.083
0.155
1.497
Factor 4
2.750
2.500
2.741
3.024
3.127
3.546
Task #2: Construct a map
Build a map using the results in Table 4. Unlike the Dell Computers case or the swimsuit example, you
will not be able to fit all four factors on one map. (Those other examples only had two factors which fit
nicely on a two-dimensional map. But here, there is no way to draw a four-dimensional map.) Select two
of the four factors and draw a map using them. Be sure to label the axes with the factor names you
came up with in Task 1. What conclusions do you draw from your map?
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MKTG 4250, Product Strategy
Sandwich shops maps (in class activity + Assignment 3)
Professor Jay Waddell
Fall 2012
What to Hand In for Assignment 3
A single, separate sheet of paper (this page is fine) containing
 The results of Part II, Task #1: the names you assigned to each of the four factors, and
 The results of Part II, Task #2: a) a map drawn using two of the four factors, and
b) a paragraph or bullet points with your conclusions from the map.
Your name:
Section time:
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