Visuals
A picture is worth a thousand words. A good graphic is worth more. Understanding multivariate relationships is an important task in multivariate data analysis. Multivariate Solutions presents clear, actionable visual approaches that help our clients interact with their data and discover the ‘Ah Ha’ data moments in each individual project. Multivariate Solutions creates an efficient workflow for multivariate analysis by employing the most useful multivariate graphical descriptive methods. Examples are shown to the right. 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.
Visuals Articles

Multivariate Solutions was featured on the Research Business Daily Report on the subject of the agile use of network analysis for social networks and collaboration.

Visualization of data networks, social media, industry structure, people analysis and organizational structures and enormous translation data is now coming online to make sense of the data deluge and convey the results of analyses through emerging, open-source programs.

Network analysis expands our core competencies such as cooperative organizational networks, brand narratives, pricing, strategic messaging, and workforce Monte Carlo projections.

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Twitter Network Analysis: Nordstrom at the Center of Resistance?, published in Greenbook, examines how visualization of social networks is now coming online to make sense of Big Data and convey the results of analyses through emerging, open-source programs.
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Michael Lieberman’s Quirk’s Marketing Research Review article, Using NodeXL to Visualize Social Media, demonstrates how to leverage social networks for promotion using the NodeXL open-source Excel add-on tool.

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.

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.

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?’.

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.

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.

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.

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.