It might surprise you to learn this - but artificial intelligence isn't a new concept. It goes all the way back to the 1950s when Alan Turing shared his ideas about a thinking machine that could grow and learn similarly to a human. The term "artificial intelligence" was first used in 1956, and since then, the way that we think about the computer has changed drastically. An article from the Harvard Business Review last year suggested that machine learning (ML) could be the most important technology we have today.
While AI obviously has a lot of roles to play in transforming the world we live in, it's safe to say that one of its most compelling areas of interest is in call centre analytics. Digital transformation and the development of new technology means that those "calls recorded for training purposes", and the information you give your consent for companies to use can be accessed in countless new and exciting ways. As Steve Tutt from Kakapo Systems said in our interview about call centre analytics: "AI definitely has a role to play."
Let's look at just some of the ways that AI have changed call analytics forever.
Capturing Important Consumer Data
Thanks to NLP (Natural Language Processing), AI can replace simplistic IVR technologies, and deliver next-level data analytics to the contact centre. In a world where voice continues to be the most popular communication method (73% of consumers call into the contact centre for their customer service needs), speech analytics gives companies a chance to access the data they may overlook otherwise.
Natural language processing is the tech that allows for call systems to automatically direct a call to the right agent when a customer calls your company. In the past, speech analytics struggled to understand consumer context and syntax. However, the growing sophistication of NLP means that systems can now interpret sentences and phrases with greater ease.
Understanding & Predicting Customer Behaviour
Speech analytics with companies like Tollring or Red Box Recorders goes far beyond what customers say these days too. It also covers "how," you say those things. Things like sentiment analysis can analyse a caller's tone, as well as the words they use to measure emotion and satisfaction levels. You can also implement algorithms that make it easier for your computers to detect caller age, which can help you to measure campaigns directed at specific user groups.
