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Biometric authentication is already a fact of life for billions of people around the world. They routinely use their faces or fingerprints to activate smartphones, PCs or other personal devices. Hundreds of millions of people with smart speakers are delighted to find that their voice assistant is able to offer personalized responses based on the unique quality of their voices. Opus Research estimates that over half a billion people have already enrolled their voiceprints with their banks, brokers, tax offices and others in order to simplify and accelerate required authentication procedures and carry out their business on trusted communications links.

When a customer reaches out to an organization, they care about one thing – getting the right information, answer, or successful and rapid completion of a transaction. Customers are not concerned about which department they are supposed to contact, only that their issue is addressed and resolved

Contrary to some science fiction movies, artificial intelligence (AI) hasn’t subjected humans to robotic overlords. And contrary to some current opinions, contact center AI isn’t all about replacing customer service agents with armies of bots.

No one would disagree that technology has improved customer service exponentially. Technology continues to enable contact centers to operate more efficiently, to be responsive in real time, and to create customer experiences that exceed their expectations, especially across an expanding array of digital channels.

As you initiate your call center software selection process, keep in mind that many new loyalty-enhancing capabilities are within your budgetary reach. Don’t set out just to replace “like-for-like.” Instead, imagine what features like new self-service capabilities, intelligent routing, and a unified agent interface could do for your customer lifetime value.

CX leaders know artificial intelligence must be part of their technology strategy—if for no other reason, to gain competitive advantage. But “artificial intelligence” is somewhat a loaded term. It encompasses a variety of applications, and it may be challenging to convince internal stakeholders of AI’s value.

The science of customer analytics has become increasingly sophisticated – so sophisticated, according to a report by Ventana Research, that organizations that try to assemble and develop their own analytics often find their customer analytics initiatives to be unmanageable and unreliable, with significant wasted time and effort and a less-than-optimal time to value.