At the point where companies measure #CSAT (customer satisfaction) they usually look at factors such as :
- #AHT (Average handling time) : how long a call center agent spends with a customer on the phone or in chat
- #FCRR ( First contact Resolution Rate) : whether the issue was resolved on the first call/chat
- #Post event surveys : what the results of follow-up customer surveys were.
However, they tend to forget about the #customerjourney :
- Did the customer need to put too much effort on the interaction?
- how did the customer actually feel?
«It doesn’t help if you call into a company with an issue and you have to repeat your name and your account number every time you are escalated to another customer service rep, or if you have trouble understanding the rep because of a language barrier,» said Dr. Skyler Place, vice president of behavioral science at Cogito
Help the agents
Whether AI will replace human customer service representatives or not is still in question. For now, AI and human agents can work togethen. AI is improving year after year. One of the growing call center trends is the increasing use of artificial intelligence software in terms of :
- smart routing
- multichannel support
- automated processes
By combining Artificial intelligence ( #AI ), #machinelearning, and big data handling and manipulation, we can help our customer service agents with some of the intangibles of customer calls :
- when a customer’s frustrations rise and they begin to raise their voice
- when there are long pauses in the conversation that could indicate rising anger.
One of the benefits of #AI is that it can be used to deal with different linguistic and cultural ways which can affect how the customer feels.
«What we are talking about is a way for the AI technology to analyze the tone of voice, or even the cadence of the language, to detect what the caller’s mood is,»
How AI can help
More and more companies have chosen to incorporate video-based and IoT sensor data in their big data initiatives : voice cadences or inflections can tell us a lot about how customers are feeling and also if they are likely to go away happy after an inteaction with a customer service advisor or they are likely to buy to your competitor.
«The idea behind the technology is to help customer service agents develop their empathy factors with customers and to make the calls go smoother,» Place said.
Inexperienced advisors can also take advantage of AI technology as they don’t have yet a natural ability to detect if a customer is happy or not. Some companies state that after implementing AI technology they saw a 28% improvement in its NPS (net promoter score), and could shortern interactions.
Remember : dissatisfied customers tend to go to a competitor.
«What the company learned was that when it used AI tools that could detect customer sentiment, it got improvement in its customer service,» Place said.
According to a recent report by Finances Online, the use of AI can help improve agent satisfaction, efficiency, and productivity as well as customer satisfaction.
«The artificial intelligence algorithms in the software actually stream in real time as the call takes place. The AI measures pauses in the conversation, how many times the agent interrupts the customer, the tone of voice of both the customer and the agent, and whether the voice is dynamic and interested or monotonal and disinterested. As the AI is doing this, it gives live feedback to the agent so they have this insight into how the customer is feeling as the call is taking place.»