Appendix 3
The details in Appendix 2 have inspired a new way of working with per-
ceptual maps. In Appendix 2, the general comparison of companies utilized
ratios. The ratios allowed for the comparison of one or more companies to
a baseline, such as a reference company. In those examples, we compared
two companies by dividing the ratings of the companies, specifically our
company divided by the comparison or competitive company. In this discus-
sion, we illustrate an analysis that uses an absolute scoring convention (i.e.,
no ratios). The final results will be mapped onto what is referred to as the
2-D weighted perceptual map.
As detailed in Appendix 2, the analysis used a questionnaire directed to
various customers. For this discussion, we will also seek the input of cus-
tomers. Customers will enter numeric values for various offering attributes.
This analysis will also use weights to gage the relative importance of the
offerings. Instead of using ratios, the scores of each attribute will be multi-
plied by the respective weights and then summed for a variety of compa-
nies. This will allow for an overall numeric score for each company. Similar
to the analysis in Appendix 2, the first analysis will be directed to customer
perceived benefits. Since we are dealing with absolutes, this quantity will be
termed absolute customer perceived benefits.
To simplify this discussion, we will illustrate the absolute customer per-
ceived benefits using an example. For this example, we will look at the attri-
bute ratings of several fictitious cellular phone providers. This example will
analyze six offering attributes, summarized:
Number of service towers (i.e., national coverage)
Download speed (i.e., 4G, 3G)
Sound quality of the phones
Phone choices (variety of appealing phones)
242 ◾  Appendix 3
Available apps
Dropped calls (minimized occurrences)
The analysis of the above attributes is illustrated in Figure A3.1. As seen
in the figure, the analysis begins with the identification of each offering
attribute along the left portion of the table. The gray shaded cells allow for
user input. First, the attributes are entered. Next, the weights are identified
for the offering attributes where the sum adds to 100%. Each attribute is then
rated for each company on a scale from 1 to 10. A rating of 0 indicates that
the attribute is not fulfilled in view of the customers. A rating of 10 indicates
full fulfillment. These entries are all based on the questionnaire provided
to customers. The rest of the table generates the final values by multiplying
each attribute by the respective weight, and then summing for each respec-
tive company. The sum produces a final value representing the absolute
perceived benefit score for each company. These values represent a set of
horizontal data points on the 2-D weighted perceptual map.
Similar to the absolute perceived benefit scores, the same logic is applied
for the absolute perceived price scores. As seen in Figure A3.2, there are
three pricing attributes that contribute to the purchase decision with respect
to cellular providers. They are outlined:
Acquisition cost (actual cost of purchasing the phone and entering into
the contract)
Monthly cost (includes cost of voice, data, texting, etc.)
Contract lock (this is primarily the cost of early cancellation of service)
For cost attributes, various customers enter the ratings on a scale from 0
to 10. A rating of 0 would indicate low pricing preference according to the
customer’s point of view. On the contrary, a rating of 10 would indicate the
best price in view of the customer. Thus, by example, a value of 10 for a
certain price attribute would indicate total customer satisfaction with respect
to that price. Similar to the analysis depicted in Figure A3.1, the values and
analysis for each companys absolute perceived price score are illustrated in
Figure A3.2.
The table depicted in Figure A3.2 is identical to that shown in Figure
A3.1, with the exception of the bottom row containing the inverse of the
sums. These values represent the vertical data points used on the 2-D
weighted perceptual map. This is necessary, as the chosen convention with
respect to price attributes would not represent actual pricing on a graph. For

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