This article was originally published on RetailTechNews and is republished here with permission.
When most companies think about a customer’s experience with a call center, there’s a persistent assumption that the support experience starts when the customer picks up the phone. I’ve always believed that view is too narrow.
By ignoring what customers have gone through before they reach for the phone, companies lose the opportunity to provide a superior customer support experience. A McKinsey study found that, in regards to participants’ customer service interactions, “more than 70% reduced their commitment when things turned sour”—proving that not focusing on a connected, intelligent approach leaves an enormous (and costly) margin for error.
Upgrade your customer experiences.Learn more
When working with our brand partners, we create an intelligent customer experience that differs markedly from the methods our partners have trusted in the past. By integrating billions of data points and engagements with marketing intel as users move through the customer life cycle, we give our teams the ability to anticipate consumers’ needs quickly and efficiently.
Our approach may be a departure from the norm, but our results have shown that integrating marketing, sales, and data science creates the best possible customer journey.
A Good Customer Experience Is Predictive
One of the most important parts of our CX approach is data. If we don’t use the right information, we get to know our customer only when they make that first call, which lets organizational silos and bureaucratic decision-making guide the process. Instead, we strive to connect each stage of the customer journey to make their lives easier.
Even if we don’t have a wealth of data about a particular customer, we can still figure out where they’ve been before they got on the phone. We just shift our mindset one or two steps back so that the support experience starts when somebody searches in Google or visits a brand’s website. Tracking the user’s online experience is perhaps one of the best ways to improve the offline support experience. Unfortunately, most people don’t know how to link those facets of the business together.
Customers are significantly more likely to repeat a story of a poor customer service experience than a good one. Those experiences could consist of anything from having to repeatedly contact a company to solve the same problem, to being led through a maze of agents who require them to repeat the same information again and again. If we have a gold mine of specific customer data that we can access, eliminating those pain points gets a lot easier. Even if we don’t have a consumer profile, we can still easily access what pages our customers just visited and see what keywords they searched. At Clearlink, we use that kind of information to predict customer intent and then provide a dynamic IVR (interactive voice response) based on that prediction.
What Predictive Experiences Can Look Like
In an ideal situation, we might receive a call from a customer, see that we’ve been good at selling them fiber internet products in the past, then geolocate their call to a fiber-qualified area and find out they’re calling from a product page packed with fiber products. Once we know that, we can route them to the agent who’s best suited to complete that sale, and arm that agent with the recommended package and offering based on what we know about the customer.
On the flip side, if we receive a support call, we look at what keywords the customer searched and the pages they visited. For example, once we know that a customer is calling from Connecticut about taxes and surcharges on their bill, we can connect them to an agent who’s really good at solving those problems—and then arm that agent with a three-step process for answering specific questions about why Connecticut state sales taxes are so high.
These kinds of processes increase customer satisfaction, reduce average handle time, and improve metrics; but we can’t do it without making a prediction about intent first.
Refining the Process
At Clearlink, we focus most on call routing—getting customers to the agent who is best able to solve their needs. Then we can give agents specific three-step solutions to issues we think a customer is having based on the data we have on those types of problems. We then evaluate: if we were right, do more of it. If we were wrong, do less. It’s a constant learning process.
We put this process into practice recently to win new business with a major telco, essentially competing against an in-house call center and an outside marketing agency to increase call volume. During the test period, we used data about keywords customers searched for related to customer service and looked at the pages they viewed, which page they ultimately visited, and what specific paracontent from which they picked up the phone and called.
We relied on that information to route calls to agents informed about where their customer had been and with the skills to answer their questions. We then dynamically changed the agents’ opening scripts to adapt to the customers’ needs. When we outsold the in-house team by 35%, that trial routine became an everyday operation as we took over all inbound sales. But the process never remains static. Fine-tuning and revisiting the customer experience should never stop.
Creating an Intelligent Customer Experience for the Long Term
Ultimately, defining and refining the intelligent customer experience is all about empathizing with the customer about the amount of energy they’ve already invested into the process. But adding empathy can’t be an objective that’s just crossed off at the end of the quarter. It needs to be ongoing.
According to Forrester, 45% of consumers said they’d walk away from a transaction if companies don’t address their needs quickly and efficiently. As of 2016, 72% of businesses considered customer experience improvements to be their number-one priority. CX improvements are crucial to remaining competitive.
Instead of treating online and offline as two totally separate experiences, think about them as one continuous experience. Right now, the person who pays for the fragmented and disconnected customer journey is the customer—and your company could lose business because of it. With the amount of data we have at our fingertips, we should be striving to be smarter, faster, and more responsive all the time.