Virtual Supermarket – Multidimensional Scaling Visual is a technique that illustrates which products customers tend to purchase together. This tool is often utilized to optimize retail space.
Multivariate Graphics
Children’s Jewish Hospital Corporate Image Visual is a two-dimensional visual regression of patient services at Children’s Jewish Hospital.
Bush Jr’s Derived Importance Among Bush Jr’s Approvers shows how Bush Jr’s fares against its main competition on important customer attributes.
Mean Drop Summary Analysis is a graphic that relates “just-about-right” (JAR) variable responses to reference variables such as overall liking in sensory/consumer research. Penalty, or mean drop, analysis is a tool used by market researchers and product developers to gain an understanding of the product attributes that most affect the propensity to purchase a new product—it is particularly useful in consumer goods and confectionery/snackfood, and food products.
Principal Components – BiPlots are, essentially, a visual factor analysis. A Biplot allows information on both samples and variables of a data matrix to be displayed graphically.
Multidimensional Scaling Maps transforms consumer judgments of similarity into a two-dimensional space, forming groups such as which products customer would purpose at a supermarket or the causes and effects of climate change.
Multidimensional Preference Maps can visually depict such queries as ‘What underlying dimensions characterize how consumers view the products?’ or ‘What is the competitive set associated with the new concept?’.
Political Correspondence Map is a snapshot of voters perceptions of a given political parties. This technique is effective when assessing many attributes with several brands or the effectiveness of advertising campaigns.
Michael Lieberman is the co-author of Marketing Research Insights: 22 Visual Displays, a compilation of practical, real-world visual display examples for enhancing market research data reports and presentations. The ebook includes sections such as Research Process, Customer Satisfaction, Competitive Analysis, Win/Loss Research, and Brand Awareness, and the charts are accompanied by usage tips.
Structural Equation Modeling (SEM) is a statistical technique for testing and estimating relationships using a combination of statistical data and qualitative causal assumptions. Among its strengths is the ability to model constructs as latent variables.
Customer Satisfaction research is a path to building customer loyalty in both consumer and B2B business markets. An actionable and action oriented approach, our customer satisfaction research techniques help build customer loyalty, market share and competitive advantage. Multivariate Solution’s senior professionals offer experience and dedication in providing high quality, reliable, useful customer satisfaction research to businesses, small and large.
Employee Relations Research
Employees are critical to the success of your business. Their opinions are necessary to ensure that your organization is functioning as you would like it to, and often can help you to improve profits. Research shows that satisfied, motivated employees facilitate higher customer satisfaction and, in turn, positively influence organizational performance. Multivariate Solutions is a leader in Employee Relations research.
