Artificial intelligence (AI) – when computers behave like humans – is no longer science fiction. Machines are getting smarter and companies across the globe are beginning to realize how they can leverage AI to improve consumer engagement and customer experience.
Gartner research indicates that in a few years 89% percent of businesses will compete mainly on customer experience. Within five years consumers will manage 85% of their relationships with an enterprise without interacting with a human – moving to the “DIY” customer service concept.
That’s why more companies are using social and digital platforms to empower customers and enhancing their contact centers with new AI technology. Interactive voice-response systems that enable agents to target and personalize communications with customers is one such example. Agents can now be armed with intelligence about why a customer is calling before even picking up the phone. The added layer of personalization and customization brings back an element of humanity that has gone missing, and it is occurring without driving up costs.
Surprisingly, consumers are even willing to pay a bit extra for such service, if need be. A 2015 poll of over 2,000 U.S. adults by Harris found that 70% said they would be willing to pay more for a brand with a good customer service reputation. Even more of them, 86%, said they would very likely switch brands after a bad customer service experience.
In many respects, AI is like a freight train racing down the tracks. Steady advances in hardware and software are sparking immense progress in how machines help interact with customers.
Google’s voice recognition technology, for instance, improved to 98% in 2014 from 84% just two years earlier. Facebook’s DeepFace technology now recognizes faces with 97% accuracy. As for IBM’s Watson, its technology is 2,400% “smarter” today than when it achieved its Jeopardy victory in 2011. Voice recognition systems themselves now perform tens of millions of online searches every month.
Consider the innovative developments in real-time speech analytics.
It’s possible, for instance, to feed a machine learning engine with all the attributes of the customer (ZIP code, product type, length of relationship, age, gender, etc.), along with the attributes of all your call center agents (level of schooling, hometown, birthdate, etc.) to determine who would serve that customer best. Then, each interaction can be quantified using any preferred metric – customer satisfaction, up-sale amount, etc.
From there, it’s relatively simple for the engine to “learn” what combination of customers and agents yields the best outcome. This method also can be used for outbound customer interactions. And over time, AI will be used to spot patterns and automatically generate alerts when an agent may be doing something that weakens the interaction, such as interrupt too much.
Additionally, AI-aided speech recognition helps improve customer service. Key words can be spotted to trigger service enhancements. The word “supervisor,” for instance, could alert a manager to join a call and alleviate any issues with a customer. Or systems can be programmed to listen for competitor mentions. With AI, healthcare organizations can monitor for words or signals that indicate a heart attack may be occurring.
Financial institutions are experiencing similar progress. Take a customer who regularly calls the bank on a Friday to check her balance. Using AI, the bank possesses the intelligence to send the customer an automated message with her bank balance before the customer picks up the phone.
By detecting behaviors and interaction patterns, a business can also choose the best channel for communicating with customers. Not every customer requires a lengthy and personal phone call. Reaching out via email or leaving an automated voicemail can prove just as effective in terms of customer satisfaction and is far less costly than a live agent phone call. It simply requires an understanding of what each customer prefers based on collected data and demographics.
From a company perspective, certain elements are critical for success with AI. These include expertise, historical and accurate customer data to understand patterns and act on them, loads of research (as illustrated with the continued investment in Siri), and cloud storage for the mountains of data being generated.
The cloud maintains data across many interactions and systems and delivers the capacity to maintain and aggregate data. This enables offline analysis across millions of customers to develop complex models. Only a few years ago, this wasn’t possible with on-premises systems.
It’s increasingly clear that AI advances are helping to bring humanity back to customer experience. Cognitive technologies are making possible:
For businesses, therefore, the return on investment incorporates all of the above, especially lower costs and the intangibles: Happier and more loyal customers.
Interactive Intelligence is a global provider of business communications and call center solutions for customer engagement and unified communications.