Consumer-Brand Relationship in the Age of Recommender Systems: Knowledge, Legacy and Guilt

Recommender systems (RS) are essential tools that support consumers in their online purchasing process by filtering products that strongly align with their needs and preferences. Moreover, they draw attention to novel items by highlighting core attributes relevant to quality evaluation. While their effectiveness in improving decision quality has been widely studied, the impact of RS on the consumer-brand relationship has received limited attention. This study adopts a qualitative approach, using Grounded Theory to analyse data from semi-structured, in-depth interviews. It investigates how recommender systems influence consumer decision-making, particularly the choice between known and lesser-known brands, by examining three key variables: breadth of knowledge, legacy, and guilt. Results suggest that consumers expand their consideration set by including unfamiliar brands, particularly for experience goods, low-involvement products and when category knowledge is limited or recommendations are perceived as repetitive and unsatisfactory. However, known brands remain particularly relevant for high-involvement products and when consumers have a strong knowledge of the category. User-based content emerges as the primary driver of choice, alongside preference matching and transparency. The effectiveness of guilt-framed recommendations is contingent upon consumers’ internalisation of norms, perceived credibility and individual sensitivity. Effective recommender systems then build trust by combining personalisation with transparency, while carefully balancing familiar and novel brands. These findings help managers understand how to use recommender systems to boost brand visibility, customer trust, and long-term reputation in online markets