2. Factor Analysis
• Factor analysis is a multivariate statistical technique that
is used to summarize the information contained in a
large number of variables into a smaller number of
subsets or factors.
• The purpose of factor analysis is to simplify the data.
• With factor analysis there is no distinction between
dependent and independent variables; rather, all
variables under investigation are analyzed together to
identify underlying factors
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6. Applications of Factor Analysis
• Advertising. Factor analysis can be used to better understand
media habits of various customers.
• Pricing. Factor analysis can help identify the characteristics of
price-sensitive and prestige-sensitive customers.
• Product. Factor analysis can be used to identify brand
attributes that influence consumer choice.
• Distribution. Factor analysis can be employed to better
understand channel selection criteria among distribution
channel members.
7. • For example, suppose that a bank asked a
large number of questions about a given
branch. Consider how the following
characteristics might be more parsimoniously
represented by just a few constructs (factors).
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10. Advantages of Factor Analysis
- Benefits include: (1) a more concise representation of
the marketing situation and hence communication may
be enhanced; (2) fewer questions may be required on
future surveys; and, (3) perceptual maps become
feasible.
- Ideally, interval data (e.g., a rating on a 7 point scale),
regarding the perceptions of consumers are required
regarding a number of features, such as those noted
above for the bank are gathered.
