Home / Resources / Six Steps of Marketing Research

Marketing Research Steps: Survey 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.

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.

 

Contact Polaris to learn more about survey data analysis.