HOW ARTIFICIAL INTELLIGENCE PERSONALIZATION INFLUENCES MARKETING STRATEGIES IN E-COMMERCE: A FOCUS ON MOROCCO

Abstract

This study investigates how AI personalization affects e-commerce marketing strategies in Morocco. With the growing local platforms, businesses are using more AI tools such as collaborative filtering, content-based filtering, and hybrid to personalize recommendation. The systems use browsing behavior, buying behavior, and demographic information to increase relevance and interaction. The research utilizes a qualitative comparative approach and makes its determinations in peer-reviewed articles, business reports, and Moroccan policy briefs. Results indicate that hybrid models of recommendations are the most flexible and precise, especially in multi-consumer settings like Morocco. AI personalization assists in customer retention, increases conversion rates, and improves user satisfaction. However, it has challenges, including privacy concerns, repetitive viewing of content, and algorithmic failure. The cold start problem and poor data protection make it even more challenging to adopt in Morocco. In order to overcome the above challenges, the research suggests ethical AI practices, open data policy, and consumer education. The research provides actionable insights to Moroccan e-commerce businesses that wish to balance personalization and data responsibility.