DYNAMIC BEHAVIOURAL SEGMENTATION IN THE DIGITAL ECONOMY

Digital technologies have changed how firms observe and classify consumers. Traditional segmentation based on static demographic, geographic and psychographic variables is increasingly unable to capture behaviour that changes from day to day on digital platforms. This paper examines dynamic behavioural segmentation, an approach in which customers are grouped and regrouped continuously on the basis of real-time digital footprints and adaptive analytics. Using a conceptual review of the literature on marketing analytics, customer experience and data mining, the paper compares traditional and dynamic approaches, proposes a six-stage conceptual model, and identifies the behavioural indicators on which dynamic segmentation relies. The analysis suggests that the approach improves targeting, supports early retention measures and shortens the response time between behavioural change and marketing action, while raising issues of privacy, transparency and data governance. The paper concludes that dynamic behavioural segmentation represents a paradigm shift in customer analytics in the digital economy.