How cognitive computing is changing customer service

Customers today want to choose the channels they interact with, and cloud and cognitive technologies make channel switching easier for all.

As real-time communications services move to the cloud, one of the biggest impacts and potential for growth revenue is coming at the intersection of software innovation and changing consumer behaviors.

After a great run for the last few decades on improving contact center enablement software, reducing the time it takes to respond to questions, reducing the traditional costs associated with toll-free support, and reducing general frustration by improving interactive voice response intelligence, service providers (including business process outsourcing companies offering customer-service-as-a-service) are having to re-think everything.

Customers are connected now more than ever before and are moving most of their personal and business conversations to messaging apps and social media.

Customers on mobile apps and the web prefer self-service over having to wait to speak with a customer service representative.

An increasing number of customers are comfortable speaking with an AI-powered bot, given the adoption of services like Siri, Alexa and other friendly assistants.

Customers expect brands to know enough about them to make targeted recommendations as Amazon, for example, already does.

Customers want choices — while at their kid’s soccer game, they may prefer to tweet a question about a feature on their smartphone, but when they are at home connecting their new entertainment system to a cable box, they may prefer to speak with a live expert.

The list goes on and on, with service applications that can make or break a brand’s popularity for being easy or difficult to interact with, beyond the quality of its products and services.

Cognitive computing is changing the face of customer service by enabling live agents to serve customers better, serving up answers in advance based on “deep listening” to the customers’ voice, level of potential unhappiness or even anger, based on the customers’ perceived tone, and connected with the customers’ account and history of previous contacts.