Influence of Artificial Intelligence Tools on Customer Satisfaction, Engagement, and Brand Loyalty within Online Brand Communities in Tunisia

Abstract

Grounded in the Technology Acceptance Model (TAM) and Social Exchange Theory (SET), this study investigates how artificial intelligence (AI) tools affect customer satisfaction, engagement, and brand loyalty within online brand communities (OBCs) in the Tunisian cosmetics sector. The research employed a mixed-methods approach that involved netnography and a quantitative survey of 250 active members of a Facebook brand community. Structural equation modeling (SEM) indicated that customer satisfaction with AI-enabled features, including personalized recommendations, automated responses, and chatbots, significantly predicted community participation (β = 0.68, p < 0.001) and engagement (β = 0.72, p < 0.001). Both participation and engagement, in turn, enhance brand loyalty (β = 0.61 and β = 0.66, respectively) and mediate the satisfaction-loyalty relationship. Qualitative data reaffirmed these results, indicating that AI-generated personalisation builds trust, emotional connection, and engagement in community interaction. From a theoretical perspective, the study adds to OBC engagement models by exploring AI enabled interactivity as an antecedent to both satisfaction and loyalty, linking two topical research domains: technology adoption and relationship marketing. Pratically, it illustrates how firms in a developing market can utilize AI based personalisation and responsiveness as a method for improving consumer-brands relationship and protecting competitive advantage.