Incorporating Offline and Call-Center Interactions into Digital Personalization: An Integrated Customer 360 Approach for B2C Sales Optimization

Abstract

Digital personalization in consumer markets has largely been driven by data from web, mobile, and other online channels. At the same time, many B2C organizations continue to rely on call centers, branch networks, and face-to-face sales interactions that generate rich but fragmented information about customer preferences and constraints. This fragmentation can lead to inconsistent treatment, misaligned incentives across channels, and suboptimal resource allocation in sales and service operations. Bridging the information gap between online and offline interactions therefore remains a central challenge for building a coherent view of the customer.  This paper examines an integrated Customer 360 approach in which offline and call-center interactions are explicitly incorporated into digital personalization logic for B2C sales optimization. The focus is on the representation, integration, and use of heterogeneous interaction data rather than on any specific software platform. Offline contacts and call-center events are embedded into a shared temporal and semantic space, enabling joint modeling of exposure, response, and purchase behavior across channels. The proposed framework links a data architecture for Customer 360 with probabilistic models of customer state and optimization formulations for contact and channel policies. It emphasizes how call outcomes, agent annotations, and branch visit patterns can adjust latent customer-state variables that drive digital personalization decisions. The discussion covers modeling detail, implementation aspects, and an illustrative scenario, while adopting a neutral stance on design choices so that the framework can be adapted to differing B2C contexts and levels of data maturity.