American Journal of Advanced Multidisciplinary Research and Innovation

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AI-Driven Customer Analytics and Personalised Services in the Digital Economy

Author(s) Gloria Yeh
Country United States
Abstract The rapid expansion of digital platforms, e-commerce, mobile applications, social media, and connected technologies has generated unprecedented volumes of customer data. Artificial Intelligence (AI) and advanced customer analytics enable organisations to transform these data into actionable insights concerning customer preferences, behaviour, purchasing patterns, and future needs. This study examines the role of AI-driven customer analytics in delivering personalised services within the digital economy. Particular attention is given to machine learning, predictive analytics, natural language processing, recommendation systems, customer segmentation, sentiment analysis, and generative AI. A qualitative and conceptual research methodology based on secondary literature is adopted to analyse how AI influences customer understanding, personalisation, engagement, retention, and organisational decision-making. The analysis indicates that AI-driven analytics can improve customer segmentation, recommendation accuracy, demand forecasting, customer-service responsiveness, and targeted communication. Personalised services can consequently enhance customer experience and potentially strengthen loyalty and business performance. However, the increasing collection and analysis of customer data creates significant concerns regarding privacy, algorithmic bias, transparency, cybersecurity, manipulation, and excessive personalisation. The study proposes a responsible AI-based customer analytics framework that combines data quality, predictive intelligence, personalisation, human oversight, transparency, and privacy protection. The study concludes that organisations should pursue customer-centric AI strategies that create genuine value for consumers while ensuring responsible and ethical use of personal data.
Keywords Artificial Intelligence, Customer Analytics, Personalisation, Digital Economy, Machine Learning, Customer Experience, Predictive Analytics, Recommendation Systems, Consumer Behaviour, Data Analytics.
Field Engineering
Published In Volume 4, Issue 4, July-August 2022
Published On 2022-08-05
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