Neural market structure analysis: Novel topology‐sensitive methodology

Over the last decade various parametric approaches toward modelling segmented perception‐preference structures such as combined MDS and latent class procedures have been introduced. These methods, however, are not tailored for qualitative data describing consumers’ redundant and fuzzy perceptions of brand images. A completely different method is based on topology‐sensitive vector quantization (VQ) for consumers‐by‐brands‐by‐attributes data. It maps the segment‐specific perceptual structures into bubble‐pie‐bar charts with multiple brand positions demonstrating perceptual distinctiveness or similarity. Though the analysis proceeds without any distributional assumptions, it allows for significance testing. The application of exploratory and inferential data processing steps to the same database is statistically sound and particularly attractive for market structure analysts. A brief outline of the VQ method is followed by a sample study with travel market data, which proved to be particularly troublesome for conventional processing tools.