Anyone who has ever called the service number of a government agency or large service provider will undoubtedly recognize it: a long wait, being transferred several times and not getting the right answer right away. Since Youp van het Hek started a Twitter storm in 2010 about T-Mobile and its, in his eyes, lousy customer service, a lot has improved in most customer contact centers. But there is still a lot of room for improvement. Because we like a challenge, we at The Analytics Lab created a dashboard that uses artificial intelligence to help companies improve their customer contact while lowering their costs.
Much of the extra cost in customer contact centers is due to unforeseen process costs. Think of additional telephone inquiries or a higher proportion of complaints. This usually leads not only to additional costs, but also to lower customer satisfaction. It often seems as if these inquiries and complaints overwhelm the call center: the nature of the inquiries and volume are unforeseen. However, unforeseen events are quite predictable with the right knowledge, business processes and the combination with artificial intelligence.
Through artificial intelligence, we can deliver a dashboard that uses predictive algorithms that can make real-time recommendations. These process improvement recommendations can be given by hourly, daily, weekly and monthly levels. Based on a self-created dataset with our data sampler, we created a first version of a dashboard to get a better grip on unexpected costs. In addition, we believe that real-time conversion of speech to text generates valuable information. This provides faster insight into the actual reason for a telephone query. Through sentiment analysis, we can also provide insight about the sentiment of each call and a psychometric profile of a caller can be created. The first version of our dashboard is now live.
Curious about our dashboard? Want to know how your company can get a better grip on customer interactions through artificial intelligence? Then take a look at the Predicting the Unplanned page or contact us.
