AI-Enhanced Consumer Insights: Leveraging Behavioural Analytics for Hyper-Personalised Marketing Strategies
Year: 2025
Type: article
Abstract: Data sources for behavioural analytics• Online interactions: websites, social media and mobile apps generate vast streams of user activity data.Clickstream analysis helps track consumer navigation paths, dwell time and interactions with digital content.The rise of multimodal AI, integrating text, image and voice data, has further enriched consumer insights, enabling more context-aware marketing strategies 11 .• Transaction history: Purchase patterns provide insights into consumer preferences and spending behaviour.Retailers use Recency-Frequency-Monetary (RFM) segmentation to classify customers based on purchasing frequency and monetary value 12 .Predictive AI models leverage transaction history to forecast future buying behaviour, enabling businesses to dynamically optimise promotional strategies 13 .• Sentiment analysis: Natural language processing (NLP)techniques analyse customer reviews, social media discussions and feedback to gauge public sentiment towards
Authors: Omotoso Oluwayomi Joseph, Akinyemi Sadeeq Akintola, Ernest Offiong, Olaonipekun Olaitan Olajuwon, Udodirim Ibem Offia, Adedayo Ayodeji Faniyan
Institutions: Universidade Nova de Lisboa, University of Worcester
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4408095423