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Advanced Statistical Analyses

ANALYSIS	DESCRIPTION	EXAMPLE APPLICATION
Multiple Regression (Driver Analysis)	Describes the relationship of each variable in a set (and the set of variables as a whole) to a single variable.	Determine key "drivers" of overall customer satisfaction with your service.
Cluster Analysis	Identifies homogeneous sub-groups within a much larger group of respondents.	Identify customer profiles or market segments, groups of customers or potential customers who make similar decisions and perceive products and services similarly.
Factor Analysis	Reduces a complicated data matrix into its more basic structural essentials.	Uncover basic dimensions employees use to evaluate how satisfied they are working for your organization.
Perceptual Mapping (Multidimensional Scaling)	Extracts multiple dimensions from a variable set and positions concepts within that space.	Visualize how customers mentally organize competitors in your product or service category and your brand's position relative to your competitors.
Structural Equation Modeling	Tests how well observed data confirm an entire theoretical model.	Describe the process by which customer loyalty is built for your particular product or service category.
Data Mining	Detects useful and sometimes unexpected patterns among variables in a data set.	Increase revenues by cross-selling your products.

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