AI-Based Customization: A Systematic Literature Review On Recommendation Agents

Consumers can nowadays rely on the support of specific recommendation agents designed to reduce search costs and increase the chance to find products and services that match their needs and preferences. Typical instances of how recommender agents are placed on e-commerce platforms are represented by statements like “you may also like…“ or " People who like this also like” that online buyers typically encounter after having completed a purchase. Although these agents are widely adopted in online shopping contexts it remains a topic that is largely not researched in the marketing perspective. With the aim to systematize the extant marketing literature on the topic we analyzed 123 papers from 54 journals. Based on the review and synthesis, we surface research gaps and provide a ten-points agenda for future research.