Performing data analysis

Any survey data analysis will depend on how the survey questionnaire was constructed. Less complex survey data analysis can be handled with any of a number of office suite tools, while more complex questionnaire data analysis requires requires dedicated market research analysis programs.

Types of statistical survey data analysis that might be performed are simple frequency distributions, crosstab analysis, multiple regression (driver analysis), cluster analysis, factor analysis, perceptual mapping (multidimensional scaling), structural equation modeling and data mining. The more complex the needed level of statistical data analysis is, the more time and cost it will take to execute.

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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