The Customer 360 Data Program: Use Cases, Architecture, and Guiding Principles
Enterprises struggle to understand and engage customers in the slippery digital world of the 2020s. A customer 360 (C360) data program can help by providing consistent views of who customers are and what, why, and how they buy. This supports campaigns that span marketing, advertising, sales, and customer service as well as analytics projects that span reporting, segmentation, requirements definition, and artificial intelligence/machine learning (AI/ML) personalization.
A successful C360 data program depends on three architectural elements—the data warehouse, customer data platform, and cloud connectors—to maintain and synchronize customer data. The cloud data warehouse integrates multi-structured customer data by ingesting and transforming it with other enterprise data in an elastic object store. The customer data platform profiles customers by building consistent models to make sense of myriad growing and fast-moving datasets. Cloud connectors activate profiles by feeding select data points to marketing, advertising, or sales touchpoints.