Polaris managers have experience across a broad range of methodologies, techniques and service categories. We have experience in all of the most popularly used statistical analysis procedures and how to design the survey instrument to optimize the benefits of those tools. We have successfully designed studies using multiple regression, discriminant analysis, cluster analyses, factor and principal component analyses, correspondence analysis, multidimensional scaling and perceptual mapping, conjoint analysis, MaxDiff analysis, structural equation modeling and a variety of data mining techniques. We know which technique is appropriate for the research task at hand, how to design the project and how to interpret the results clearly and concisely with little use of technical jargon.
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ANALYSIS
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DESCRIPTION
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EXAMPLE APPLICATION
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| 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 us to learn more about how Polaris can assist you with all types of advanced statistical analyses.
