Factor Analysis

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Factor Analysis
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Factor Analysis

• A data reduction technique designed to represent
  a wide range of attributes on a smaller number of
  dimensions.

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Factor Analysis

• 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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Factor Analysis
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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.
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• - 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.

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Cumulative percent of variance explained.
We are looking for an eigenvalue above 1.0.
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What shall these components be called?
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EXCLUSIVE
TRENDY
RELIABLE
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Calculate Component Scores
EXCLUSIVE
(Expensive Exciting Luxury Distinctive
Conservative Family Basic)/7
TRENDY
(Appeals to Others Attractive Looking Trend
Setting)/3
RELIABLE
(Reliable Latest Features Trust)/3
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Not much differing on this dimension.
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Cluster Analysis
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Cluster Analysis

• A mechanism for grouping objects, frequently used
  for segmentation.

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How would you group these faces?
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Vacation Anyone?
Relaxation
Distant Vacation
Adventure
Historical
Local Vacation
No Vacation
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Cluster Analysis

• It would be possible to run factor analysis and
  then examine clusters after this.
• Two fundamental types of clustering exist (1)
  hierarchical and, (2) k-means.