AI-Powered Personalization in Fast-Moving Consumer Goods Marketing: Evaluating Consumer Outcomes and Ethical Trade-Offs

This study investigates the impact of AI-driven personalization on consumer engagement, satisfaction, and ethical perceptions within FMCG marketing. Employing a mixed-methods approach, it integrates qualitative data from expert interviews with quantitative responses from 391 participants to assess both the potential and limitations of AI personalization strategies. Thematic analysis highlights AI's capacity to facilitate adaptive, real-time marketing and enhance short-term engagement. However, it also reveals persistent challenges, including over-personalization, privacy concerns, and diminished consumer autonomy. Quantitative analyses found no significant associations between AI personalization and customer loyalty or satisfaction, nor between AI use frequency and perceived effectiveness. Notably, only AI’s predictive accuracy showed a weak but significant relationship with customer satisfaction, suggesting limited explanatory power for traditional personalization metrics. Ethical concerns and privacy risks emerged as key drivers of consumer skepticism, reinforcing the need for transparency and data control. The findings challenge assumptions that personalization alone drives customer loyalty and call for context-aware, ethically grounded marketing strategies. FMCG marketers are advised to adopt hybrid models that balance technological capabilities with consumer trust, autonomy, and long-term engagement.