We are in an era of omnichannel commerce, where consumer behavior is changing rapidly in unexpected ways and ever-evolving. Retail and consumer product companies must get better at anticipating and responding to new consumer needs and preferences. The companies need to reimagine how to engage with consumers in very different, more targeted, and niche oriented ways.

Consumers are using various retail touch points to purchase products and contact a company for service and support. Retail and consumer product companies can get a complete view of their consumers by aggregating the relevant data from such touch points to acquire a 360-degree view of the consumer. Mobile devices, online communities, social media platforms, and more, has resulted in a boom in the number of touch points for customer interaction. Without the right tools, this can pose a serious challenge in aggregating the data from the many diverse interactions that consumers may have across channels. A true 360-degree view needs to include views of the past, present and future in a meaningful and easily digested view of the consumer. It includes product or policy activity, interaction history across all channels, community, recent product views, campaign activities and process history. The present requires presenting key consumer information about who they are and how they relate to your organization; and determines the context of consumer interaction. Is there a recent order or current fault, why are they interacting with us now? The future relates to actions that can be initiated to guide the future of relationship. Is the consumer likely to churn? Are there up-sell or cross-sell opportunities or targeted product messages aligned to the needs of consumer?

The reinforcement learning AI platform developed by ICURO brings in consumer interactions about the products and services, analyzes and correlates real-time data of consumer sentiment and competitive positioning from social media and other data sources. The AI system learns from deep consumer engagements and identifies behavior patterns. The predictive intelligence measures the heath metrics of consumer from loyalty economics and cost of bad experiences standpoint. The deep learning algorithm prescribes value to the consumers, implements timely market promotions, and analyze success in real time predictive marketing.