PERSONALIZATION OF MARKETING OFFERS AND RECOMMENDER SYSTEMS IN SOCIAL E-COMMERCE: A MODEL OF CONSUMER TRUST FORMATION

Abstract

This article examines how personalized marketing offers and recommender systems influence consumer trust in social electronic commerce. The purpose of the study is to develop a conceptual model of trust formation that combines technological, behavioral, and platform-related determinants of personalization. The research is based on content analysis of recent academic publications, comparative analysis of leading digital platforms, and scenario-based interpretation of consumer behavior in online purchasing environments. The authors’ contribution consists in systematizing contemporary forms of personalization, summarizing the main types of recommender systems, distinguishing typical buyer scenarios, and developing an integrated trust model for social electronic commerce. The paper reviews product recommendations, adaptive interfaces, personalized communications, conversational assistants, and data-driven promotional offers. It also summarizes collaborative, content-based, hybrid, knowledge-based, and socially informed recommender models and explains their role in reducing search costs, improving choice relevance, and shaping trust toward the platform and the seller. Special attention is devoted to the conditions under which personalization strengthens trust and to the situations in which it produces a backfire effect because of privacy concerns, intrusiveness, low transparency, or weak content authenticity. The study identifies several typical consumer scenarios in social commerce, including the new buyer, the loyal buyer, the hesitant buyer, and the skeptical buyer, and proposes differentiated personalization strategies for each scenario. The scientific novelty of the study lies in the integration of recommender-system logic, social-commerce trust drivers, and user behavior into one coherent analytical framework. The proposed model shows that trust grows when personalization is relevant, explainable, controllable by the user, and supported by institutional safeguards and social proof. At the same time, the model demonstrates that excessive or opaque personalization can weaken trust even when short-term conversion indicators improve. The practical significance of the study lies in the possibility of using the proposed framework for designing ethical and effective digital marketing communications, refining recommendation policies, improving transparency tools, and strengthening long-term customer relationships in social electronic commerce. The article concludes that personalization should be treated not only as a conversion instrument but also as a mechanism of relationship building that requires balance between relevance, privacy protection, and consumer autonomy.