Omni Channel Customer Engagement

Customers interact with companies in a multitude of channels that span Mobile Apps, Web self service, IVR, email, partner channels, direct sales, customer service, physical locations, and social media. In many cases these interactions tend to be disjointed because most organizations have different systems to support each channel with minimal integration between those systems. As a result, customers are often frustrated when engaging a company because their actions in one channel are not factored into the interaction in the next. Studies have shown that these types of disjointed consumer interaction problems are a bigger detriment to customer loyalty than customer dissatisfaction with your products and services.

An Omni-Channel approach provides a seamless converged customer engagement model across channels and products. It ensures that customer interactions are on a continuum of engagement where each channel has full visibility to previous interactions regardless of origination and what starts in one channel can continue effortlessly in another.

Dante has been on the leading edge of delivering frictionless Omni-Channel experiences across Digital channels and Physical locations. To power these solutions, Dante leverages a combination of microservices, location based engagement, cross channel event correlation and orchestration, and big data analytics to develop a complete view of the customer engagement and serve customer needs accordingly.

At Dante, we recognize that your customers are unique in their preferences, behaviors, and needs. To that end, we have developed extensive personalization capabilities to support the Omni-Channel engagement model. Our personalization algorithms range in scope from market segmentation based on customer characteristics and expressed preferences; to inferences based on customer behavior and actions of similar customers. We combine the effective use of business rules based market segmentation with inferences using machine learning and big data analytics to derive likely interests and actions.