For Better Customer Service, Look into the Future
In this day and age, companies are expected to be able to address problems before the customer even becomes aware of the issue. That requires them to have some predictive capabilities, which is proving to be a challenge, but not an impossibility.
Predictive capabilities are commonplace in marketing and sales, but less so in customer service. After all, customer service teams already have enough to do responding to the growing number of customer contacts that come in over a growing number of channels, including phone, email, text, chat, social media, and more. And with operations so severely disrupted by COVID-19 and the shutdowns that it spawned, many companies are having a hard time just trying to keep up with current demand, let alone being proactive with customers.
Most customer support teams have done reactive service pretty well, and 27 percent of them across industries improved their customer experience scores this year, according to Forrester Research’s 2020 U.S. Customer Experience Index. Consistently meeting the needs of customers has given them enough wiggle room to engender a little good will even when they make a minor mistake. But, to truly get customers to love them unconditionally, companies need to be proactive.
Predictive customer service is fundamentally different than predictive marketing and sales, experts say, noting that marketing and sales are about anticipating what customers would like to buy, while the service element typically kicks in after the customer has already made the purchase.
“When a customer service department receives a complaint, they aren’t trying to sell a product because the customer has already purchased the product,” says Dennis Reno, senior vice president of customer experience at Cyara. “Instead, the customer service team is attempting to maintain customer loyalty by quickly and efficiently resolving any issue [customers] might be experiencing.”
Maintaining this kind of brand loyalty depends on what happens after a sale is made, adds Charles Hicks, general manager of Sugar Serve, SugarCRM’s customer service platform.
It’s no surprise, then, that corporate leadership across industries is calling for customer service departments to be more proactive in their outreach rather than waiting around for customers to start calling.
Among the chief benefits of proactive service, according to Bill Donlan, executive vice president and digital customer experience leader at Capgemini, is reduced costs.
Donlan says that with the right artificial intelligence technologies, contact centers can identify issues and resolve them before they become problems, which reduces the number of support calls that customers have to make.
But it’s not just the C-suite that sees the value in proactive support. A recent consumer study by Kustomer found that 76 percent of consumers expect companies to be proactive in reaching out and following up with them when they have a problem.
In survey after survey over the past few years, consumers have repeatedly said they would be happy to be contacted proactively about customer service issues, especially about fraudulent activity on their accounts, upcoming appointments and similar reminders, and issues related to orders they’ve placed.
Practicing predictive, proactive customer service requires a combination of deep customer knowledge, the right technology, and empowered customer service agents.
THE ROLE OF DATA
Experts agree that implementing predictive customer service begins with data. The challenge, however, is bringing this data together to identify emerging trends.
That’s not easy, given that most contact center metrics on the market today look at operations reactively rather than proactively.
This is a big problem for Hicks, who points out that most contact center analytics are designed to provide insight into customer issues after the fact.
“By the time churn rates and resolution times indicate an issue, many customers are probably already considering alternatives,” he says.
Another common pitfall is that companies might only be gathering data from channels that they deem essential, says Rick Blair, vice president of product strategy and experience management at Verint Systems.
“They instrument the most important channels and think, ‘Well, those are the most critical ones,’” he says. “When shifts occur, you don’t see it when it spills over to a channel that’s not being measured and monitored.”
The other piece is having the data to be able to build those models, Blair says. “If you’re not instrumenting, you’re not collecting the data, and you’re not going be able to create the models themselves.”
Data also might not be shared between company teams.
“Companies have so much data, and it is often being managed in silos,” says Charlie Moore, vice president and general manager of customer experience solutions at SMG. “Customers are interacting with companies across more touchpoints than ever before. Connecting those problems within the customer journey gives internal support teams the insights they need to resolve customer problems quickly and accurately.”
Blair agrees, highlighting one of Verint’s retail customers that recently ran a campaign set to expire at a certain hour, but never specified whether that was in the Eastern or Western U.S. time zones. Not surprisingly, customers on the West Coast were a little miffed when they tried to respond only to find that the promo codes didn’t work.
“That’s something that could go unnoticed for quite a long time if the digital team and the customer service side of the organization aren’t sharing that information,” he says.
For this reason, companies must ensure that data is shared between their teams, via tools such as real-time alerts.
“It’s a whole other thing entirely when you’re able to wire the organization together so that the data can flow back and forth, so something that’s an emerging trend in one channel can be shared with others, especially when you can immediately identify it as applicable,” Blair says.
Implementing tools that promote connectedness between channels to develop a more complete view of the customer is essential for companies’ predictive customer service efforts.
SugarCRM’s answer to this is what it calls high-definition customer experience (HDCX). It aims to address common problems in CRM systems in general and customer service initiatives in particular, specifically a low-quality view of the customer based on incomplete, inaccurate, and/or outdated information, according to Hicks.