Módszerek összehasonlítása

	Kano-modell	Perceptual Mapping
Tudományterület	Ember–számítógép interakció	Marketing Science
Módszercsalád	Hypothesis test	Process / pipeline
Keletkezés éve	1984	1997
Megalkotó	Noriaki Kano	J. Douglas Carroll & Paul E. Green (multidimensional scaling in marketing)
Típus	Two-dimensional model categorizing product/service features by satisfaction impact	Dimension-reduction pipeline for visualizing brand positions in a low-dimensional perceptual space
Alapmű	Kano, N., Seraku, N., Takahashi, F., & Tsjui, S. (1984). Attractive quality and must-be quality. Journal of the Japanese Society for Quality Control, 14(2), 147–156.	Carroll, J. D., & Green, P. E. (1997). Psychometric Methods in Marketing Research: Part II, Multidimensional Scaling. Journal of Marketing Research, 34(2), 193-204.
Alternatív nevek	Kano Analysis, Attractive-Performance-Basic Model	Brand Mapping, Positioning Maps, Product Space Maps, Perceptual Space Analysis
Kapcsolódó	3	3
Összefoglaló	The Kano Model is a framework for categorizing product or service features based on their impact on customer satisfaction. Developed by Noriaki Kano, this model distinguishes three types of features: basic (must-have) features that satisfy minimally but cause significant dissatisfaction if absent; performance features that increase satisfaction proportionally with their level; and attractive (delightful) features that exceed expectations and generate disproportionate satisfaction. By classifying features using the Kano Model, product teams prioritize development efforts, balance risk and innovation, and design experiences that delight rather than merely satisfy.	Perceptual mapping turns how consumers see a set of brands into a picture: a low-dimensional space in which nearby brands are perceived as similar and the axes summarize the perceptual dimensions that organize the category. Two families of techniques produce these maps. Attribute-based mapping starts from brand-by-attribute ratings and uses dimension reduction — principal components, factor analysis, or correspondence analysis — to place brands and overlay attribute directions as a biplot. Similarity-based mapping starts from consumers' direct judgments of how similar brands are and uses multidimensional scaling (MDS) to recover the space, requiring no attribute list. J. Douglas Carroll and Paul Green's 1997 Journal of Marketing Research review codified MDS as a marketing tool, and Green is widely regarded as a central figure in bringing scaling and clustering to marketing research. Adding consumers' ideal points or preference vectors converts a perceptual map into a positioning tool that reveals where demand concentrates and where white-space gaps lie. Because the map summarizes competitive structure, it complements choice-based views of market structure such as those from latent-class choice models. The result is a single diagram managers use to diagnose positioning, spot competitors, and find opportunities.