Enhancing customer value through artificial intelligence and machine learning: Personalization, big data analytics, and customer experience management
Abstract
The development of the Artificial Intelligence and Machine Learning technologies has altered the process of organizational Customer Value creation, delivery, and maintenance in becoming more competitive digital marketplaces. Conventional Customer Relationship Management and traditional Customer Experience Management solutions tend to be incapable of handling large volumes of consumer data, providing Real-Time Personalization and providing dynamic responses to shifting Consumer Behaviour. This has seen organizations trend towards using Big Data Analytics, Predictive Analytics, Recommender Systems, Conversational AI, and Generative AI, to enhance Customer Satisfaction, Customer Loyalty, Customer Retention, and Customer Lifetime Value. This review of the literature serves to systematically study recent studies on the impact of Artificial Intelligence, Machine Learning, Personalization, Big Data Analytics and Customer Experience Management on improving Customer Value. Keywords such as AI-Driven Marketing, Customer Engagement, Omnichannel Experience, Behavioural Analytics, Digital Customer Experience, Sentiment Analysis and Recommendation Engines were used to identify relevant studies in major Scopus and Web of science indexed databases. The results show that AI based Personalization Algorithms, Real-Time Analytics, Natural Language Processing, Deep Learning and Customer Segmentation are proven to enhance customer engagement and quality of service in retail, e-commerce, banking, healthcare, and hospitality, among other industries. The Customer Journey optimization and service innovations are also redesigned with emerging technologies such as Emotion AI, Explainable AI, Human-AI Interaction, Adaptive Marketing and Smart Retail. But Privacy, Data Security, Ethical AI, AI Governance, Consumer Trust, and algorithmic bias are some of the issues that have led to challenges in sustainable implementation.
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References
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Copyright (c) 2026 Adejoke Olumide Dele-Rotimi (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c) 2025 International Journal of Applied Resilience and Sustainability (IJARS) 
This work is licensed under a Creative Commons Attribution 4.0 International License.