Segmentation And Positioning For Strategic Marketing Decisions

Segmentation and Positioning for Strategic Marketing Decisions

Useful to both consumer marketers and business-to-business researchers, this detailed and engaging book delves much more deeply into segmentation than other marketing handbooks. Myers mediates between discussing the intricacies of segmentation and positioning techniques and showing the ways these techniques can be interpreted and used in the real world. The book covers measuring scales, cluster analysis, conjoint analysis, multivariate analysis, CHAID, and classification and regression trees. Other chapters deal with perceptual positioning maps-point and vector, value maps laddering techniques, and quadrant analysis. Myers uses examples to explain research analysis and provides practical information. In addition to explaining how to evaluate results, he provides caveats and explains pitfalls of each technique.

Segmentation and Positioning for Strategic Marketing Decisions

Market Segmentation Analysis

This book is published open access under a CC BY 4.0 license. This open access book offers something for everyone working with market segmentation: practical guidance for users of market segmentation solutions; organisational guidance on implementation issues; guidance for market researchers in charge of collecting suitable data; and guidance for data analysts with respect to the technical and statistical aspects of market segmentation analysis. Even market segmentation experts will find something new, including an approach to exploring data structure and choosing a suitable number of market segments, and a vast array of useful visualisation techniques that make interpretation of market segments and selection of target segments easier. The book talks the reader through every single step, every single potential pitfall, and every single decision that needs to be made to ensure market segmentation analysis is conducted as well as possible. All calculations are accompanied not only with a detailed explanation, but also with R code that allows readers to replicate any aspect of what is being covered in the book using R, the open-source environment for statistical computing and graphics.