Customer experience and behaviors are described mostly in hindsight, not in real time, and not on an individual or microsegment level. Predictive propensity models and prescriptive clustering are high level, not providing insights nor contextualized real-time next best action recommendations.
Goals and Objectives
Enables the ability to see quickly and comprehensively how different kinds of content perform in different channels and settings and make changes based on insights, increasing the potential of enhancing customer engagement and retention
Cloud platforms for data management and analytics; customer data networks; machine learning/AI; natural language processing; personality, behavioral, and conversational tone analytics; affective computing; social network analytics; and predictive and next best action analytics
Use Case Summary
Customer engagement and behavior analytics enable descriptive, predictive, and prescriptive access to customer insights from internal and external data that media companies can use to provide hyper-personalized programming that is relevant and engaging.