Having recently made a $940 million acquisition of Sandy, Utah-based inContact, you'd think Paramus N.J.-based NICE Systems would have its hands full. And let's not even get started about its new product roadmap, which it will be rolling out over the course of the year.
But nope. NICE is also gunning to solve one of the more frustrating problems in the contact center industry, which is agent turnover.
Its premise is astoundingly, forehead-slapping simple: loop agent center managers — or at least what they know about agent behavior — into the HR process to select the prospective agents. So if contact center managers have noticed that agents with certain personality characteristics tend to quit after one week or one day of training (and that happens), the hiring process will screen for those qualities.
Conversely, contact center managers also can tell the personality characteristics that make a particular agent best suited for sales, for instance, or to handle tech desk calls from frustrated customers.
To be sure, there is plenty of advice out there about how to hire a call center agent that won’t quit on you — and little wonder.
Overall attrition for the call center industry ranges between 30 percent to 45 percent, with some contact centers experiencing a full 100 percent attrition rate each year, industry statistics show. A rare few have single-digit attrition.
So the advice has been coming fast and furious. Suggestions include: develop detailed on boarding plans. Provide clear paths to promotions. Make their work spaces as ergonomically correct as possible. Empower the agent to settle down angry customers.
All of these have merit but they don't get at that core problem, which is that contact centers are hiring the wrong people in the first place.
The 'Right' Software + the 'Right' Agent
Here, one should note that NICE has more than a vested interest in making sure that contact centers hire the "right" agent. After all, these agents will be trained on, and eventually will operate its software solutions on behalf of NICE's customers.
What's more, NICE's next iteration of its software is even more "agent focused" — as the industry likes to call these user interfaces — than its current incarnation, according to execs presenting at the annual conference the company held in Orlando, Fla., earlier this year.
Or as Miki Migdal, president of the NICE Enterprise Product Group, told the audience, technology continually reinvents the notion of best-in-class customer service.
Contact center solutions are the focus now but wait a few years, he said. "Machine learning customer service bots will be the next big thing."
Yet funnily enough, he continued, "in challenging times customers look for the human element."
Challenging, in this context would mean a bill that is, say, $500 more than expected or something along those lines — any scenario, in short, in which even the most tech-oriented, self-service using customer's first instinct is to reach for the phone to rant and rave at a live human being.
The plan, or hope, is that he gets the 'right' agent when he does.
A Grand, Interactive, Seamless Vision
But let's put aside this notion of selecting the right agent from the get-go for just a moment to look at NICE's grand vision as it works on its next iteration of its flagship system and related products.
It is a work in progress — the products will be rolling out throughout the next twelve months — of applications that are infused with intelligence, productivity and an empowered agent (that is, someone who can make decisions to resolve a customer matter on the first go).
Instead of doing a deep dive on the individual products and their underlying technology, let’s go back to that irate customer with the $500 bill mistake. NICE used that as an example in one of its demos for the next iteration of its Adaptive Workforce Optimization product line, first introduced last November.
A Customer Journey Starts With a $500 Mistake
This particular customer journey begins with a call from a customer to her wireless provider asking about service overseas for a trip she is planning. "Not a problem," she is told — roaming charges don’t apply. However, when she gets home and sees a bill of about $500 more than she was expecting, she realizes this was grossly inaccurate.
She posts an angry tweet about the bill — duly noted by NICE's system — and then calls in to resolve the issue.
NICE has gathered all the relevant information, from her first call to the company to the tweet to the bill, and has it ready to give to the appropriate agent (someone who has been identified as having a particularly soothing manner with annoyed customers).
The agent and customer figure out what went wrong — it was a miscommunication that was technically the customer’s fault as she did not say she was going to be traveling in multiple countries across multiple continents — but the agent decides that the previous rep really should have asked these questions specifically before he told her that roaming charges weren’t an issue.
This second rep credits her the amount and then cycles that information into the system so that the next agent handling a call about traveling and roaming fees knows to specifically ask about the countries involved.
Hence Migdal's description of the new adaptive WFO suite. "The agent persona is at the heart of everything."
Applying Analytics in the Call Center
To be sure, contact center apps have been using advanced computing to best match agents with callers for some time. Last year Forrester analyst Art Schoeller described two case studies from vendors Mattersight and Satmap (now called Afiniti) in which behavioral analytics were used in the contact center get a better outcome.
He wrote: "Satmap helped one of the largest telecommunications carriers in the United States boost sales conversion rates by 6 percent, driving $100 million in incremental revenue over a two-year period. The trial included alternating periods of turning Satmap on, and then off, to provide outcome comparisons. CVS Caremark adopted Mattersight Predictive Behavioral Routing and was able to drive an 8.4 percent reduction in average talk time during their proof of concept trial. CVS is also using the data to better target training and coaching to agents."
What is interesting here is that NICE is taking that same concept — that same flow of analysis, intelligence and information-sharing and applying it to hiring the right agent with the goal of the better outcome of agent retention.
Instead of the information about questions that the agent should have asked, the system will have information about reps that have succeeded and what their common factors are. Or what they told their hiring manager about their preferences for learning styles or schedules or work hours.
Behavioral analytics is then able to pick and choose reps that are right for a particular assignment — such as a "soothing" rep brought in to speak with a fuming customer.
Think of it as another form of driving incremental revenues.