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Companies frequently offer product recommendations to customers, according to various algorithms. This research explores how companies should frame the methods they use to derive their recommendations, in an attempt to maximize click-through rates. Two common framings—user-based and item-based—might describe the same recommendation. User-based framing emphasizes the similarity between customers (e.g., “People who like this also like…”); item-based framing instead emphasizes similarities between products (e.g., “Similar to this item”). Six experiments, including two field experiments within a mobile app, show that framing the same recommendation as user-based (vs. item-based) can increase recommendation click-through rates. The findings suggest that user-based (vs. item-based) framing informs customers that the recommendation is based on not just product matching but also taste matching with other customers. Three theoretically derived and practically relevant boundary conditions related to the recommendation recipient, the products, and other users also offer practical guidance for managers regarding how to leverage recommendation framings to increase recommendation click-throughs.

Companies frequently allow customers to customize products by assembling different product features or ingredients. Whereas existing research has demonstrated that customers assign greater overall value to customized products, this research focuses on the effect of customization on customers’ perceptions of specific product attributes (e.g., how healthy a product is). The findings of six studies—in the field, laboratory, and online—demonstrate that customizers and noncustomizers differ in their product perceptions even if the product is objectively the same. This is because customization leads customers to perceive the product in line with their own self-image (e.g., as an unhealthy eater), a phenomenon that the authors term “self-image-consistent product perceptions.” Essentially, customization may influence product perceptions depending on the product and individuals’ self-image; this can have downstream consequences on recommendations and social media communication. The authors test this theory for different product categories (clothing, food, and vacation packages) and attributes (fashionable, healthy, and adventurous) and demonstrate that framing customization as a simple choice or strengthening product positioning through labeling mitigates negative effects of customization.

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