© 2018 Cengage Learning®. May not be scanned, copied or duplicat.docx

© 2018 Cengage Learning®. May not be scanned, copied or
duplicated, or posted to a publicly accessible website, in whole
or in part.
© 2018 Cengage Learning.® May not be scanned, copied or
or in part.
15.
1
15
Marketing Research Tools
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15. 2
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15.
2
Marketing Framework
3

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15.
Discussion Questions #1
How can you find the answers to the following questions?
How will your targeted customer respond to a price of $7.99
compared to $9.99?
Should you add a new feature that costs $4.00?
Which is a more effective slogan: “We love to see you smile” or
“Have it your way”?
4
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15.
Marketing Research
Marketing decisions should be fact-based
Smart marketers are continually gathering market information
Marketers also conduct specific research projects
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Marketing Research Techniques
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Marketing Research Process
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Kinds of Data
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Popular Research Techniques
Cluster analysis
Perceptual mapping
Focus groups
Conjoint analysis
Scanner data
Surveys
9
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15.

Cluster Analysis
Clustering
Form groups within groups of customers, who are seeking
something similar and different across groups
Each group has different attributes
Often used for segmentation
10
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15.
Cluster Analysis Example
(slide 1 of 4)
Segmentation of NPO supporters
Desired result: Determine if segment exists that may donate to
an NPO that funds higher education
Start with a survey
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15.
(slide 2 of 4)

Survey used to interview customers
12
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(slide 3 of 4)
NPO dataset
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(slide 4 of 4)
Next, conduct cluster analysis
C1 cares about environment, but not much
C4 cares about medical causes; thinks higher ed is expensive
and would support students
C2 cares about the arts; thinks higher ed helps society
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15.

Cluster Analysis Questions
Which segment is most attractive for the NPO to target? Why?
15
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15.
Perceptual Mapping
Positioning studies are used to understand customer perceptions
of brands in the marketplace
Perceptual maps assist in positioning
They give pictures of competing brands and attributes
Two approaches
Attribute-based approach
Multidimensional scaling (MDS)
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15.
Perceptual Mapping: Attribute-Based
(slide 1 of 2)
In attribute-based perceptual mapping
Customers complete a survey
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Perceptual Mapping: Attribute-Based
(slide 2 of 2)
Responses on each question are averaged
Result is a pair of means for each attribute
e.g., BeFit Gym is perceived as a good value
The pairs of means are used to plot the attributes in a two-
dimensional space
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15.
Perceptual Mapping Questions #1
Which attribute is most important?
How does BeFit Gym score on this attribute relative to
competitors?
Which attribute should BeFit Gym consider improving? Why?
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15.
Perceptual Mapping: MDS
Multidimensional scaling starts by asking, “How similar are

these two brands?”
Asks for each pair of brands
Then, each brand is rated on attributes
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15.
Perceptual Mapping Questions #2
Which brands are viewed as most similar?
Which brand is the most different?
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15.
(slide 1 of 3)
Results are then plotted
Similar brands are closer together; different brands are further
apart
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15.

(slide 2 of 3)
Next, overlay the perceptual map with the attribute ratings
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(slide 3 of 3)
Feature
fun classes
in ads
Feature staff
in ads
Show fun amenities
MDS can be used to determine how to reposition the brand
24
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15.
Focus Groups
(slide 1 of 2)
Focus groups

Used for concept testing & ad development
Exploratory technique using 2–4 groups of 8–10 customers
Not good for prediction; best to follow up with a survey
Usually last 1.5–2 hours
25
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Focus Groups
(slide 2 of 2)
Focus group moderator
Starts with introductions and easy questions
Proceeds to key client questions
Keeps the discussion going
Brings out quieter members
Controls overbearing members
Moderator usually analyzes results along with company input
26
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15.
Discussion Question #2
Describe at least two research techniques to answer the
following objective: How will customers respond to our new
packaging?
27

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15.
Conjoint Analysis
(slide 1 of 2)
Conjoint studies
Used to understand how consumers make trade-offs
Helps uncover customers’ most important product attributes
Good for pricing, new products, branding, etc.
e.g., Would frequent fliers in a loyalty program want access to
an elite club at large airports?
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15.
Conjoint Analysis
(slide 2 of 2)
Participants rate each option from least to most preferred
What feature do customers want?
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15.
Conjoint Analysis Questions #1

Fliers’ judgments are in the last column
Describe how the customers’ preferred option differs from the
2nd most preferred.
What does this difference mean to marketers?
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15.
Conjoint Analysis Questions #2
Regression is run on data with flier ratings as the dependent
variable
Predicted rating = 5 + 1 Club + 2 Upgrade – 4 Fee
How would you interpret this?
How would you design your program based on these results?
31
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15.
Scanner Data
(slide 1 of 4)
Companies use scanners to track purchase information and store
it in a database
Tracked information includes:
What you bought
How much you bought
What brands you bought
How much you paid for everything

Loyalty cards then link this information to each customer
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15.
Scanner Data
(slide 2 of 4)
Store and area auditors integrate additional information into
database
e.g., Prices of competing brands, sales/featured items,
advertised brands
Companies can add data from customer panel who provide
household information and agree to have their media tracked
These data, with the other tracked data, determine purchase
patterns
33
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15.
Scanner Data
(slide 3 of 4)
Scanner data can be used to forecast demand and determine
responses to marketing changes
Experiments with scanner data
Increase price by X—what happens to sales?
Manipulate independent variable (price); hold all else constant;
measure impact on dependent variable (sales)

Compare sales results to control group
High internal validity
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15.
Scanner Data
(slide 4 of 4)
Naturalistic observation with scanner data
Instead of manipulating environment, just constantly monitor
Things happen that are beyond your control
e.g., Competitors raise price
High external validity
More difficult to attribute sales differences to one localized
action
Smart companies do experiments and naturalistic observation
35
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15.
Surveys
(slide 1 of 2)
Surveys
Often used to measure customer satisfaction, repurchase
intentions, etc.
To administer
Write survey questions
Pretest them
Administer to a sample of customers

Analyze results
36
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15.
Surveys
(slide 2 of 2)
Survey considerations
Surveys can be administered in person, over phone, on the Web,
etc.
Surveys should be short to enhance response rate
Responses should be confidential
Responses should not be used for subsequent sales opportunities
Respondents can be consumers or B2B
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15.
Surveys—Factor Analysis
Factor analysis is utilized to simplify variables
Factor analysis examines strong and weak correlations to
identify underlying factors common to the responses
High correlations imply that you may be measuring the same
concept
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15.
Which items hang together?
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15.
What would you label Factor 1?
What would you label Factor 2?
40
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15.
You developed an idea for a new shoe: Having a single shoe
sole in which you can clip on different shoe tops to create
different shoes (the Onesole).
Describe appropriate research techniques to answer each of the
following questions.
Is this concept viable?
Which will generate more sales: one pair of soles and one shoe
top for $30, or one pair of shoe soles and 3 shoe tops for $50?
41

or in part.
15.
Managerial Recap
(slide 1 of 2)
Cluster analysis identifies similar customer groups—ideal for
segmentation
Surveys and MDS are used to create perceptual maps—ideal for
positioning
Focus groups are exploratory—ideal for product concept and ad
testing
42
or in part.
15.
Managerial Recap
(slide 2 of 2)
Conjoint methods indicate trade-offs—ideal for product design
Scanner data—ideal for investigating brand switching, loyalty,
price sensitivity, and marketing experiments
Surveys—ideal for satisfaction
Can be simplified through factor analysis
43

or in part.
15.
© 2018 Cengage Learning®. May not be scanned, copied or
or in part.
or in part.
1
14
Customer Satisfaction and Customer Relationships
or in part.
14. 2
or in part.
14.
2
Marketing Framework
3

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14.
Does customer satisfaction matter? Why or why not?
How do you determine whether you are satisfied?
4
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14.
Customer Evaluations
(slide 1 of 3)
Customer evaluations include
Customer satisfaction
Perceptions of quality
Customers’ intentions to repurchase
Customers’ likelihood of word-of-mouth, etc.
Marketers track these evaluations because they impact the
bottom line
5
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14.
(slide 2 of 3)
Customer Evaluations =

Experience − Expectations
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14.
Evaluation Outcomes
If customers’ experiences
Low-involvement purchases
Evaluation is instantaneous
Expectations are usually latent
Higher-involvement purchases
Evaluation is deliberative and conscious
7
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14.
(slide 3 of 3)
Search goods
Evaluate obvious qualities; straightforward
Experiential purchases
Evaluate after trial/consumption
Expectations might not be fully formed; the experience shapes
evaluation & expectations
Credence purchases

Don’t have expertise to evaluate
Evaluate what one can (price, looks, etc.)
8
or in part.
14.
Sources of Expectations
Personal experience
Consumers trust their own experience
Experience can be direct or indirect
Friends and experts
Trust those with no commercial gain
Marketing mix elements
Ads, price, retail atmosphere, etc.
Third-party communications
e.g., Consumer Reports, books, and Internet
9
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14.
Expectation and Experience
The core (hygiene factors) and peripheral components
(motivating factors) of a product both contribute to satisfaction
If the core is good, it doesn’t enhance satisfaction much because
it is expected to be good
If the core is bad, it can affect dissatisfaction
Peripheral services can affect both
10

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14.
Expectation & Experience: Flowcharts
Marketers create flowcharts that map all of the interactions
between the customer and company
From the eyes of the customer
Flowcharts are used to
Generate quality measures at each stage
Identify points of repeated problems
Suggest system redesigns to improve efficiency
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14.
Types of Expectations
Ideal levels of quality
Predicted levels of quality
Adequate levels of quality
Zone of tolerance exists between the adequate and predicted
levels of quality
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14.
Customer Value
Value
The trade-off of the quality of the purchase received compared
to the price paid and other costs incurred

Marketers try to increase perceptions of value
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14.
Expectations
Expectations are dynamic
What pleased a customer last time may no longer suffice
Expectations vary cross-culturally
In individualist cultures, satisfaction is heavily influenced by
quality of reliability and service provider responsiveness
In collectivistic cultures, satisfaction is heavily influenced by
the relational aspects of frontline employees
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14.
Measurement
Measuring quality with precision is difficult
Customer perceptions can be measured with surveys
Compare results to previous or competitive benchmarks
Surveys that measure multiple facets of customers’ thoughts are
more actionable
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14.

Customer Dissatisfaction
The primary means to regain a dissatisfied customer is through
empowered frontline employees
Immediately redress the problem
Empathize with customer
Offer a perk for customer’s troubles
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or in part.
14.
Customer Relationship Marketing
(slide 1 of 2)
Customer satisfaction is first step in
long-term relationship
Loyalty programs
Price discounts may keep customers from defecting while
inducing additional purchasing
Some companies may assume loyal customers are price
insensitive and charge them more
17
or in part.
14.
Customer Relationship Marketing
(slide 2 of 2)
CRM programs track customer information including RFM

information
Recency, frequency, and monetary values of customers’
purchase history
These factors are used to “score” customers to identify the most
desirable customers
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or in part.
14.
Describe the most desirable customers according to the figure.
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14.
Customer Database Information
Contact information
Demographics
Lifestyle and psychographic data
Internet info
Transaction data (RFM, etc.)
Rate of response to marketing offers
Complaints
20

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14.
CRM
CRM programs
Take planning and money
Require ongoing customer monitoring
Companies struggle to design an information system with
desired qualities
Integrate inputs from all relevant customer touch points
Access information in useful formats for managerial usage
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or in part.
14.
Customer Lifetime Value
(slide 1 of 2)
Companies utilize customer lifetime value (CLV) to assess
customers in terms of their worth to the company
Some customers are costly to acquire, others more costly to
retain
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14.
Customer Lifetime Value
(slide 2 of 2)

23
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14.
Customer Lifetime Value Example
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14.
Managerial Recap
(slide 1 of 2)
Quality and customer satisfaction can be precisely measured for
goods, but not as easily for services
Surveys can be used to ask customers for their evaluations of
any purchase
Marketers care about loyalty and customer relationship
management
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or in part.
14.
Managerial Recap
(slide 2 of 2)

Customer lifetime value is a means of translating marketing
efforts into financial results
CLV allows firms to match customer benefits to revenues to
ensure that each customer relationship remains profitable
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or in part.
14.

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