How Machine Learning Can Help Businesses Leave Bad Customer Service In The Dust

Each time a customer support representative interacts with a customer, they create data that can be used to improve their products and services. Although that type of data is important, there’s another kind of data that’s just starting to be analyzed: immediate feedback on how a customer really feels. On the surface, they may appear calm and complacent, but they could be more upset than they let on.

Recent studies have revealed that people prefer to troubleshoot their own problems and only call customer service as a last resort. By the time a DIY consumer calls customer support, they’re more than likely upset. Customer service representatives understand that people who contact them for help might be frustrated or even angry, and they’re trained to do everything they can to resolve the problem and de-escalate a customer’s anger. That starts with reading the customer.

Reading people is a skill naturally developed through daily interactions with others. Still, many customer service reps receive extended training to help them read people better.

This extended training is necessary because some customers hide their true feelings and do a good job of appearing satisfied when they’re actually upset. This is a problem for customer service reps because they won’t have the chance to make things right for the customer. A customer who walks away upset is more likely to take their business elsewhere or post a negative review online.

How do reps miss the cues of an upset customer? Sometimes those cues are subtle, and invisible to the naked eye.

Body language doesn’t always reveal everything

Phone support representatives are at a big disadvantage “ they have to rely on tone of voice to provide clues beyond what a customer shares. Agents who connect with customers in person have an easier time navigating their interactions. They have the opportunity to read facial expressions and body language. Though, that’s not always enough.

Even the most well-trained customer service representative can miss the microexpressions that can give away a customer’s real feelings. Microexpressions are brief facial expressions that come and go in the blink of an eye. According to experts, microexpressions reveal a person’s deepest emotions, especially ones they’re trying to hide.

Although most people don’t have the cognitive ability to spot microexpressions, some do. It turns out that while most people are entirely oblivious to microexpressions, says TechnologyReview.com, a tiny subset of individuals can spot them accurately and use them to tell whether people are hiding their true feelings or when they are downright lying.

Machine learning can help reps read microexpressions

Real-time facial expression detecting systems have been in development for decades. These systems were developed with machine learning to recognize microexpressions of neutrality, anger, disgust, fear, joy, sadness, and surprise. You can read about one such system here.

This technology provides an advantage to businesses providing virtual customer service through video. A business could run expression detection software alongside their video conferencing software to identify microexpressions displayed by customers. This would give the representative an advantage in resolving the customer’s issue on the spot. For example, if the software indicates that a customer just displayed a microexpression of anger, they can immediately redirect the customer to neutralize the anger before it escalates.

The idea of using video conferencing as a means of support is the future. As businesses face the challenge of meeting customer demands with limited resources, more are turning to methods of virtual support.

For instance, a company called IVCi deploys practical solutions for businesses to extend their customer service and utilize personnel resources efficiently. Partnering with Cisco, IVCi created a video conferencing customer support solution for First Financial Credit Union in Chicago. The credit union was struggling to meet their members’ needs.

Some branches had longer lines than others, and not enough personnel to assist. So, they employed a virtual video conferencing option for customers to connect with available service reps from another branch. The goal was to improve member experience, and there’s no doubt that’s been accomplished.

We have four branches, so it’s always been a struggle for us to make sure we have proper staffing, says Michael Abraham, CEO of FFCU. There are times when some locations are super busy, and others that aren’t. We needed to figure out how we could utilize our staff across the locations to better serve our members.

The future of customer service is in technology’s hands

When service reps know exactly when their customers start to feel angry, they can immediately offer them a special deal, or bend the rules to retain their loyalty. It’s all about timing. If they wait to respond to a negative review, it’s already too late.