Detalhes do Documento

Enterprises increasingly seek to optimise digital products using predictive artificial intelligence (AI) that anticipates customer behaviour rather than merely reporting it. This paper proposes and evaluates an integrated predictive-AI framework for enterprise product optimisation that unifies five capabilities usually pursued in isolation: behavioural modelling, customer-acquisition analytics, process intelligence, intent prediction, and personalised decision-making. The central thesis is that these capabilities compound when built on a shared feature and event foundation, converting fragmented analytics into a coherent optimisation loop. Using a design-science methodology triangulating a representative behavioural dataset, controlled predictive-model evaluation, and an A/B-style comparison against a non-personalised baseline, the study quantifies behavioural-prediction accuracy, acquisition-conversion uplift, process-bottleneck detection, intent-prediction performance, and the business effect of personalised decisioning.....