2. Topics To Be Covered
Introduction
Stages
Objectives
Managerial Uses
Unique Features
Assumptions and Limitations
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3. Conjoint Analysis
Conjoint analysis attempts to determine the relative
importance consumers attach to relevant attributes and
the utilities they attach to the levels of attributes.
The respondents are presented with stimuli that consist
of combinations of attribute levels and asked to evaluate
these stimuli in terms of their desirability.
Conjoint measures attempt to assign values to the levels
of each attribute, so that the resulting values or utilities
attached to the stimuli match, as closely as possible, the
input evaluations provided by the respondents.
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4. Conducting Conjoint Analysis
Formulate the Problem
Construct the Stimuli
Decide the Form of Input Data
Select a Conjoint Analysis Procedure
Interpret the Results
Assess Reliability and Validity
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5. Objectives
To establish a valid model of consumer judgments
useful in predicting the consumer acceptance of any
combination of attributes, even those not originally
evaluated by consumers.
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6. Conjoint Analysis and Marketing
Conjoint analysis is a versatile marketing research technique that
can provide valuable information.
Which new products will be successful?
Which features or attributes of a product or service drive the
purchase decision?
Do specific market segments exist for a product?
What advertising appeals will be most successful with these
segments?
Will changes in product design increase consumer preference
and sales?
What is the optimal price to charge consumers for a product or
service?
Can price be increased without a significant loss in sales?
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7. Managerial Uses of Conjoint Analysis
1. Find the product with the optimum set of features
2. Determine the relative importance of each feature
in consumer choices
3. Estimate market share among products
4. Identify market segments
5. Evaluate the impact of price changes or other
marketing mix decisions.
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8. Unique Features of Conjoint
Specifying the Conjoint Variety
The only data provided by the subject is the dependent
variable. The independent variable is pre specified.
Separate Models for Each Individual
A unique model is specified for each individual.
Predictive accuracy is made for each individual.
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9. Assumptions and Limitations of
Conjoint Analysis
Conjoint analysis assumes that the important attributes of
a product can be identified.
It assumes that consumers evaluate the choice
alternatives in terms of these attributes.
Data collection may be complex, particularly if a large
number of attributes are involved and the model must be
estimated at the individual level.
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