Memory-based models of predicting inferences about brand quality

How are consumers’ inferences about product quality related to brand information in memory? Prior literature suggests that, in vast majority of cases, consumers tend to assign higher quality to the products they have seen or heard of before than to those they do not recognize. People’s tendency to assign higher value to the objects they recognize has been documented in many areas outside consumer product domain as well. However, people sometimes deviate from this tendency. This work investigates the reasons behind these deviations and suggests a psychological model that builds on the idea that perceived product quality should be viewed not as a point estimate, but as a distribution of beliefs about quality. By modelling inferences, as well as confidence in inferences, via belief distributions, this paper aims at explaining some unsolved phenomena regarding the relationship between quality perceptions, on one side, and recognition and other memory information, on the other. First, it tries to find out whether the belief distributions reflect the relationship between brand quality perceptions and recognition (as well as other memory cues), documented in the marketing literature. Second, using belief distributions, it attempts at explaining why people sometimes infer that an unrecognized brand is of higher quality than a recognized brand. Finally, it investigates whether the belief distributions predict inference and confidence in inferences better than existing models. In an attempt to answer these questions, we conducted lab studies comprising over 35,000 individual inferences.