Excellent customer service is increasingly becoming a critical factor for businesses. In this world of omni-channel service, providing the right information — fast — requires a properly maintained knowledge base. Accurate responses are what good service is based on. Then voice analysis comes in to ensure continuous improvement. That’s a solid foundation for agents who deal with customers to build on; understand customers, act accordingly, and you’ll be able to wow them. Emotion analysis helps achieve this goal.
Voice recognition software works in a similar manner to facial recognition. Much in the way facial recognition systems measure facial features to find a specific individual they match, voice recognition software can reliably identify words and phrases. Subtle differences in pronunciation can result in completely different meanings. For instance, many speakers do not pronounce the final ‘t’ in the word ‘can’t’ at all, making it difficult to distinguish from ‘can’. The software, however, hears small differences in vowel length to correctly understand words and tally their frequencies. This provides the gist of what is being said, allowing service centers to categorize customers according to the content of their requests. Take interactive voice response (IVR), for instance. Voice-activated menu systems have the ability to analyze the voice and emotions of a customer as they describe their issue and direct the caller based on these insights directly to the correct agent or team according to the topic of the request.
Great significance for call centers
It’s important to note here that to protect customer privacy, advance permission is required before recording calls. If permission is granted, speech recognition software can be used to generate word lists from the recorded conversations and determine which words were used the most frequently. From these lists, insights can often be gained for use in future customer interactions. But it’s not just lists with frequently used words, but phrases as well that can be extracted from calls using LVCSR analysis (large vocabulary continuous speech recognition). This technology makes it possible to detect the topic of the conversation and reveal which phrases were repeated the most. The data obtained in this manner can then help the company optimize its products. But these insights can also be used in the contact center to improve the conversational skills of agents. Software that identifies emotions takes things to the next level.
How good are you at sizing people up?
We’ve all been there. You think you understand how someone else feels about something, only to find out later you had it wrong all along. Experienced agents get this right most of the time, but if they don’t, it can have serious consequences. To allow call centers to be as responsive as possible to customers, software that identifies emotions is now in use.
This software not only understands and analyzes the content of conversations, it also detects the caller’s mood. The accuracy of these systems is now in the range of 85-93 percent. Agents see a traffic light during the conversation that represents the customer’s mood. Having that information in front of them reassures the agent, because they are now able to better estimate the customer’s mood. Agents are instructed to first address the emotions and ask questions.
That should make the customer feel they are being taken care of and increase their satisfaction. In addition, the agent can see their own mood to better regulate themselves. The benefits this type of software offers have made it increasingly popular. But it’s important to use it to support agents, not as a means of supervising them. Otherwise, you risk their traffic light going to red more often. This type of software also shows great potential for improving service quality. The emotion recognition results can for instance be used to help assess customer satisfaction without having to ask the customer about their feelings directly.
Speech recognition software and software that identifies emotions can help to make service more personalized, which is a sustainable way of increasing service satisfaction levels. As artificial intelligence continues to make inroads in many areas of the modern enterprise, customer service also stands to benefit from analysis bots over the long term.
More information on service center success is available at: www.getsabio.com