(untitled) (International Journal of Engineering & Extended Technologies Research (IJEETR), 2024)
Digital interaction ecosystems have created many architectural challenges for enterprises in terms of managing, synchronising and activating customer intelligence across multiple distributed systems and interaction channels. Traditional infrastructures for customer engagement tend to suffer from disjointed identity stores, disjointed behavioural data, and batch processing models that hinder scalability, slow down personalization responsiveness, and prevent coordinated delivery of the customer experience. In the age of real-time engagement strategies, there’s a growing demand for scalable architectural patterns that allow enterprises to integrate identity resolution, profile computation, and orchestration across channels in a continuously adaptive digital ecosystem This paper proposes a common customer identity and customer profile architecture to meet the requirements of real-time enterprise orchestration by distributed identity resolution, streaming event processing, scalable customer profile computation and low latency activation frameworks. The proposed architecture is capable of a 94% identity match accuracy, achieving profile freshness latency of less than 2 minutes for batch window of 480 minutes as compared to the conventional batch-oriented models, and cross-channel consistency score – 54% to 91%. Implementation results, across telecommunications, retail, financial services and media, showed reductions in activation latency of between 60% and 74% and improvements in personalisation accuracy of between 76% and 92%. The framework delivers an extensible and privacy-enabled approach for enterprise-wide customer intelligence orchestration which can be used for support AI-assisted decisioning, predictive audience modelling and adaptive journey orchestration