Intelligent Data Platforms For Personalized Retail Analytics At Scale

Abstract

Intelligent Data Platforms (IDPs) represent a transformative concept for enterprises striving to continually personalize product, message, and experience offerings across the customer journey, at scale. The notion reflects the data and analytic capabilities enabling organizations to drive personalization through automated, data-driven processes dedicated to delivering tailored experiences across all interactions with customers—both online and offline.

These platforms incorporate specialized components for customer data integration, customer 360-degree generation, segmentation and profiling, behavior-based personalization, experimentation, and trust-related applications—ranging from data quality and lineage to compliance with privacy policies. They integrate with the IT landscape for support functions such as enterprise service management and data governance, thereby helping retail organizations establish processes for a systemic delivery of personalized experiences.

Alongside a description of the key components of an IDP, the relevant wholesale architecture principles for supporting personalized breadth, depth, and freshness of individual offerings are explored. The discussion covers the essential ability to exploit customer-centric personalization implicitly throughout a retail business model—alongside demand-driven forms of personalization involving active multidimensional segmentation.