"You need to be able to take all the information from the contact center and all the other data points within the organization and use them to identify the appropriate action for serving the customer. You need to be able to find the common themes to pull together what customers are complaining about, to tell what's going on and how to fix it."
Convery says the benefits go beyond even that. With predictive capabilities, companies will be able to see not only how they can make their contact centers more efficient, but understand the effect of even the littlest change. "You want intelligence to tell not only what is happening now, but the downstream outcomes of it," she says.
Solutions are also getting better at incorporating context into their decisions. "We're seeing contextualized interactions, looking not only at the content of the current interaction but everything that came before it," says Keith McFarlane, chief technology officer at LiveOps, a provider of cloud-based contact center and telephony platforms.
This could be particularly helpful in curtailing repeat calls, according to Dick Bucci, founder and principal analyst at Pelorus Associates. A customer, he says, might be repeatedly calling for the same reason, and, until recently, contact center analytics had no way of uncovering that information.
"There's a lot of data that could identify an at-risk customer," he says, "and now we can [use analytics] to draw a profile of that customer. Once you've got the data, you can use it to put together the correlations. Then you can see where things are going, whether they're trending up or down and why, and take the appropriate action to correct it."
Dowlaty states that more companies are showing an interest in predictive and contextual solutions. "We're seeing a rise in intelligent [analytics] systems," he says. "It's not just about why customers are calling, but anticipating their needs."
Companies will naturally flock to these types of solutions, Fluss adds. "There is finally an understanding that if you are proactive, you can save both time and money," she says.
The Democratization of Data
But for contact center data to be actionable in this way, it can't be locked up in the IT department, which has been the case with many failed contact center analytics initiatives of the past. Fortunately, prevailing market conditions and the ultra-competitive landscape in which most businesses find themselves today have brought about a dramatic shift.
Organizations of all sizes are sifting through larger and more complex data sets to make routine business decisions, and to do this, they have asked for business intelligence solutions that let users visually explore data and create reports that are easy to understand.
As vendors have unleashed their new wave of contact center analytics solutions, the prevailing trend has been to make analytics insights accessible to the everyday employee, no longer just those with data science backgrounds. Vendors have simplified their user interfaces, libraries, search results, and reports. "With new visualizations, a human can consume the information," Dowlaty boasts. "You want to take IT out of the equation, and now I can build out the data on my own. I can be very agile with the data on my own. I can search it on my own."
That's not to say that the IT department shouldn't have a role. "Today you need to partner with IT in new ways," NICE's Storm says, "especially to protect the data without restricting access to the information and insights."
At most companies, data from contact center analytics now has to flow both upstream and downstream. The contact center manager, obviously, needs access to the analytics data, but the same information can also be helpful to front-line agents and back-office personnel. Even C-level executives are seeking it.
"When contact center analytics first came out, it was for data people. Now executives are getting reports daily and looking at them. Executives are bringing contact center data front and center," OpenSpan's Convery says.
Considering this, it shouldn't be surprising that contact centers are growing in strategic importance within the larger corporate structure. Contact centers today are expected not only to uphold the company's brand image and reputation, but also to positively affect company revenue and profits. For these reasons, analytics is playing a key role in becoming "a strategy changer within the organization," Convery observes.
Dowlaty says not enough companies are at this stage, though. "It's still a fairly young movement to bring the contact center in on decision-making," he says. "The big data trend is moving us in that direction, but only leading companies are doing this now."
Not surprisingly, LiveOps' McFarlane sees this mostly among larger firms. "Larger companies, especially those with robust big data strategies in place, have already gotten to their [contact center] data and are using it to predict trends," he says.
In general, contact center analytics technology "is definitely getting better, but many organizations still need to figure out how to use it," Fluss says. That isn't necessarily an insurmountable challenge.
"Contact centers have been throwing off big data for as long as they've been around," she adds. What's different now is that, "for the first time ever, we have the tools and the know-how to be able to capture and evaluate every single customer touch point, enable the organization to understand what is happening, and take action to change or correct it at the time of the interaction."
News Editor Leonard Klie can be reached at firstname.lastname@example.org.