Customer data is often siloed across departments, of poor quality (incomplete, old, held in inconsistent taxonomies, locked in unstructured formats, etc.), and not analyzed or modelled for clustering, propensities, or lookalike patterns. Some use of third-party and consortium data, but little use of social graph, geospatial, and other new data types and sources. CX KPIs are
Goals and Objectives
Maintain comprehensive, current, and consistent customer data assets harvested from enterprise, partner, social media sources and made available to CRM, marketing, and demand management applications. Consume and mix traditional transactional, structured web interactions, and unstructured text and voice interaction data. Publish data assets to decriptive, predictive and prescriptive analytical applications in customer care, hyper-personalized marketing, and curated merchandise design and assortment use cases.
Natural language processing, advanced statistical predictive and optimization analytics, sentiment and behavorial modelling, other AI tools, high-scale database applications, data lakes, and data management platforms.
Use Case Summary
Provide data and analytic foundation for all omni-experience customer engagement use cases and customer-centric use cases under other strategic priorties.