Using Sentiment Analysis to Improve Your Customer Service

If you’ve ever puzzled over a text message or email, wondering if the sender was joking, being sarcastic, or was being completely serious, you’ve encountered one of the biggest unsolved problems of the Digital Era. You know exactly what the other person said, but that doesn’t always help you understand how they actually feel. Interpreting “sentiment” — emotions, attitudes, and other subjective expressions — can be a difficult task even for trained customer service rep, but computers are absolutely hopeless at it.

Until recently, that is. A major breakthrough in business technology called “sentiment analysis” now allows companies to accurately gauge the mood of their customers. By applying this technology to popular support solutions, like Zendesk, businesses can finally take the guesswork out of their most important customer communications.

Most sentiment analysis solutions use sophisticated machine learning algorithms to scan through a given customer communication, such as a support ticket submission or chat log. By identifying keywords and phrases in that communication, sentiment analysis tools can then determine the overall emotional disposition of the customer. This allows a customer service rep to understand the general mood of the customer — positive, negative, neutral, or mixed — before engaging with them.

How it Works with Support Teams

It’s not hard to understand the value of this kind of insight in a support context. Support teams can use sentiment analysis to quickly scan ticket submissions, for instance, flagging the most disgruntled customers for urgent responses from the most skilled reps. By analyzing changes to sentiment on a message-by-message basis, reps now have some objective indication that they’re actually resolving the customer’s issue. Records of these interactions — as well as message-by-message sentiment changes — also allow for highly detailed training documents, providing reps with real-world examples.

As with any new business technology, there’s also no shortage of confusion about what sentiment analysis can actually achieve in an everyday setting. It can’t read your customers’ minds, for instance, and it also can’t transform a poorly trained customer service team into a well-trained one. It can provide extremely valuable, real-time insights about how your customers feel, but it’s not a magic wand. De-escalating a furious customer who is livid about a real issue with your products or services still requires good, old-fashioned customer service. What sentiment analysis tools can do, however, is provide a powerful tool for knowing if your customer support staff, training, and strategies are actually successful.

What are the core elements of a professional-grade sentiment analysis solution? Here are five key principles to keep in mind when considering sentiment analysis technology for your business.

Accurate analysis:

Above all else, the system needs to be good at recognizing the keywords and phrases that indicate the current customer sentiment. It also needs to clearly indicate that sentiment to the support rep. This is trickier than it sounds, particularly for a computer, requiring proven machine learning technology.

Real-time insights:

The system should be able to automatically analyze messages as they are sent. This allows the support rep to observe changes in sentiment — both positive and negative — as they happen.

Tracking sentiment:

Customer sentiment rarely changes over a single message, or even a single conversation. It happens over an entire interaction; from the moment a ticket is submitted to the resolution of the issue. Great sentiment analysis tools track changes to mood over the entire interaction. It allows reps and trainers to understand success and failure on a moment-by-moment basis.

Integration ready:

Sentiment analysis tools aren’t meant to be standalone systems. They need to work with your existing customer support solutions, and even be fully integrated with them. If your company uses a common customer support solution, like Zendesk, your sentiment analysis tools need to play nice with them. Consider using a dedicated integration or plugin.

Scalability:

Your support technology needs to be able to grow with your business. Many developers of sentiment analysis tools lack the expertise and resources needed to build a truly scalable solution.

Sentiment analysis is still a new technology. Yet, it’s fast becoming an essential one for any business with a growing customer base. If retention and customer satisfaction matter to your company, it’s worth taking a serious look at sentiment analysis.

Next Steps

Looking to uncover and address inefficiencies in your customer experience processes and your Zendesk software? Register for a Zendesk efficiency review!