As a liberal arts major in college, there is nothing I like better than invoking the spirit of The Bard (Shakespeare) in my writing. My title borrows from one of my favorite of his comedies, As You Like It. At a high level, I believe cloud contact center applications using artificial intelligence allow companies to deliver the kind of customer experience their customers want – not one dictated by the constraints of hardware-based, inflexible applications.
In the customer experience space, we started talking seriously about artificial intelligence (AI) less than five years ago. The notion of chatbots emerged and soon after had its first major “fail.” In March 2016 a Microsoft AI-powered bot called Tay was launched and quickly shut down due to concerns with its inability to recognize when it was making offensive statements.
Bad news? No, actually, it was good news. Nothing progresses without trial and error. The industry went back to the drawing board with a new awareness of the power of machine learning – and how to better use its power for good, not evil. Chatbots have become a great example of how AI is used in customer-facing applications. What has become more interesting for me, especially in 2019, is the heightened awareness of how AI can and is being deployed to improve customer experiences “behind the scenes.”
One slide (shown here), used at an April 2019 industry analyst meeting I attended, helped educate me on the wide range of applications of AI in contact center and workforce application solutions. While many of the capabilities described here may look futuristic, they are for the most part features available from NICE and NICE CXone today - and in use by customers.
Several capabilities that assist in the management of contact center agents are listed. The use of AI in forecasting and scheduling likely sounds like manna from heaven for the countless companies that still rely on Excel spreadsheets – often with a complex set of embedded macros - to do their weekly agent schedules. AI in workforce management is almost required to handle the complexities of today’s omnichannel contact center. No spreadsheet or macro is enough to deliver schedules that can simultaneously maximize support for up to 30 different real-time or messaging interaction channels with a pool of agents with as broad a variety of skills.
Automated quality assurance (QA) takes the notion of analyzing 100% of interactions using speech analytics to a new level. For several years, companies have been adding speech analysts to quality management applications with great success. Until now, that has meant providing the application with the specific metrics and keywords that should be flagged for review.
With automated QA, combined with automatic topic categorization, unplanned issues or atypical agent activity can be highlighted – emphasis on the word unplanned. An agent who always remembers to complete a call with a compliance-required phrase suddenly misses it on several calls in a row. While quality management may have picked that up over the course of several days, AI-driven quality assurance can bring management attention in near real-time.
In the agent category of the uses of AI behind the contact center scenes, next best action jumps out as bringing enormous value. With all the potential reasons a customer may be calling, it takes more than an agent’s perusal of a customer record to zero-in on the most likely reason a customer is calling NOW and what they may need.
Four years ago, in an Enterprise Connect presentation, I highlighted the wonderful work NICE was doing in next best action, specifically with identifying the reasons a new mobile phone buyer might be calling into the contact center with a few days. At the time, that kind of functionality was available only to the very large mobile carrier or financial institution who could afford to invest millions in custom solutions for next best action.
Today, thanks to the move of contact center software to the cloud and the advances made in artificial intelligence, an advanced capability like next best action has become democratized. No longer available only to contact centers with tens of thousands of agents, next best action is something the mid-sized contact center could easily incorporate into their centers now.
I hope I have piqued your curiosity about the ways you could begin bringing AI to life in your company. Join NICE CXone’s Laura Bassett and Tamsin Dollin for a webinar, The AI-enabled Contact Center, to hear even more.