Integrating Artificial Intelligence into Digital Marketing Strategies to Enhance Customer Personalization, Brand Trust, and Repurchase Intention

Abstract

The increasing adoption of artificial intelligence has transformed digital marketing by enabling automated interaction, customer-data analysis, predictive recommendations, and personalized communication. This study examines the effects of AI integration on customer personalization, brand trust, and repurchase intention, including the sequential mediating roles of personalization and trust. A quantitative explanatory design was employed involving 200 consumers who had interacted with AI-supported digital marketing features, including chatbots, personalized advertisements, automated recommendations, and predictive offers. Respondents were selected through purposive sampling, and data were collected using a five-point Likert-scale questionnaire. The measurement and structural models were evaluated using partial least squares structural equation modeling with bootstrapping. The findings demonstrate that AI integration positively influences customer personalization and directly increases repurchase intention. Customer personalization significantly strengthens brand trust, while brand trust positively affects customers’ intention to purchase again. The sequential mediation analysis further confirms that AI integration increases repurchase intention partly by creating relevant personalized experiences that subsequently develop customer confidence in the brand. These results indicate that technological sophistication alone is insufficient to maintain customer relationships. Businesses should combine AI capabilities with transparent data practices, secure information management, accurate personalization, and customer-oriented communication. Such an approach enables firms to improve digital marketing effectiveness while building trustworthy relationships that support sustainable customer retention and repeat purchasing.