Relating brand confusion to ad similarities and brand strengths through image data analysis and classification. (English) Zbl 1414.62495
Summary: Brand confusion occurs when a consumer is exposed to an advertisement (ad) for brand A but believes that it is for brand B. If more consumers are confused in this direction than in the other one (assuming that an ad for B is for A), this asymmetry is a disadvantage for A. Consequently, the confusion potential and structure of ads has to be checked: A sample of consumers is exposed to a sample of ads. For each ad the consumers have to specify their guess about the advertised brand. Then, the collected data are aggregated and analyzed using, e.g., MDS or two-mode clustering. In this paper we compare this approach to a new one where image data analysis and classification is applied: The confusion potential and structure of ads is related to featurewise distances between ads and – to model asymmetric effects – to the strengths of the advertised brands. A sample application for the German beer market is presented, the results are encouraging.
MSC:
| 62P20 | Applications of statistics to economics |
| 62H30 | Classification and discrimination; cluster analysis (statistical aspects) |
| 62H35 | Image analysis in multivariate analysis |
Keywords:
brand confusion; confusion experiment; image data analysis and classification; multinomial logit model; two-mode hierarchical cluster analysisReferences:
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