|Category||Consumer, Marketing Intelligence|
|Keywords||Brand Management, Artificial Intelligence|
Understanding consumers’ associations with brands is a central part of brand management. It is a challenge for brand management agencies and large FMCG companies managing their own brands. Consumers associate a brand with multiple objections, emotions, activities, and concepts.
The researchers developed an AI-powered Brand Visual Elicitation Platform (B-VEP) that allows companies to collect and analyze online brand collages from consumers.
Using unsupervised machine-learning and image-processing tools, the researchers analyzed the collages to obtain a detailed set of associations for each brand. Using the power of visuals to depict a detailed representation of respondents’ relationships with a brand, the elicitation is direct, unaided, scalable, and quantitative. The tool helps to obtain:
- prototypical brand visuals
- relating associations to brand personality and equity
- identify favorable associations per category
- explore brand uniqueness through differentiating associations
- identify commonalities between brands across categories for potential collaborations
Association extraction methodology combines beyond state-of-the-art text-mining methods. B-VEP can be used to support both the creative function and the strategic function of the brand management team. For the creative function it provides a prototypical collage, or a mood board, for each brand insights. For strategical functions it is useful in assessing brand health, competition relative to other brands as well as collaboration opportunities.