Kosmo Karantonis

This study examines the predictive validity of implicit evaluative brand association measures in real market outcomes and the boundary conditions of their effectiveness. Drawing on dual-process theories, we focus on the Implicit Association Test (IAT) as a tool for capturing subconscious brand associations. The research questions ask whether IAT-based brand image scores can predict actual market share and how this relationship might vary with key product category characteristics, specifically, consumers’ consideration set size and purchase frequency. We conducted a large-scale survey of toothpaste brands measuring implicit brand associations via the IAT and linked these scores to each brand’s market share data. Hierarchical regression analysis showed that implicit brand image significantly predicts market share in the product category. Moreover, the IAT’s predictive validity was stronger when the consumer’s consideration set was small, consistent with intuitive decision-making playing a greater role under low choice complexity. However, the expected moderation by purchase frequency was not supported, frequent, habitual purchasing did not further amplify the IAT–share link. Overall, the findings demonstrate that implicit measures can enrich brand equity assessment by capturing hidden drivers of brand preference that translate into market performance, especially in low-complexity choice contexts.

This study introduces and validates a novel quantitative survey-based technique (select-and-rank, SAR) designed to measure brand preference as an outcome of consumer-based brand equity (CBBE). The SAR method combines simplicity with predictive accuracy by leveraging a ranking-based approach leaning on a Zipf distribution—a model demonstrated to effectively represent market shares. Its development addresses the need for a practical and reliable tool in large-scale brand studies, distinguishing itself from traditional methods by offering improved measurement capabilities and reduced cognitive load. Using data from a market representative sample, this initial study demonstrates SAR’s ability to accurately capture brand preference dynamics while comparing its performance against widely used existing measurement techniques. The findings reveal SAR’s enhanced accuracy, robustness, and scalability, making it a valuable addition to the CBBE research toolkit. The study also highlights managerial implications, offering brand managers a technique to capture consumer preferences to assist in optimizing brand positioning and strategy in competitive markets. Finally, recommendations for future research are provided to extend SAR’s application to additional dimensions of CBBE.