This paper aims to expand the domain of brand image perception measurement by providing a method for eliciting brand associative networks and comparing it with traditional brand image measurement methods. This paper then argues that these networks may differ from one individual to another, depending on the cultural background and/or the experience with the brand. Accordingly, the authors introduce a methodology of clustering consumers with similar perceptions into distinct segments, which can be targeted differently. Using picture analysis and metaphors-based d¡citation techniques, Upton's Ice Tea brand associations are extracted and utilised as an input for the creation of I 60 individual associative networks. These networks are first aggregated to measure the brand reputation and subsequently clustered into six segments. This paper provides dear arguments for using associative networks as the preferred method to capture the complete brand image. The paper discusses implications of perceptual segmentation for image management, brand positioning, perceptual competition analysis and brand communication.
CITATION STYLE
Rojas, R. (1996). Associative Networks. In Neural Networks (pp. 309–334). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-61068-4_12
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