AI Powered Call Analytics: Let the Machines Do the Talking
Mastering the power of machines for the call centre
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.
Essentially, AI has the power to enable new levels of customer assessment and understanding. It allows companies to assess how their customers feel, and potentially predict their behaviour through various stages of the buying cycle. This could help call centre managers to train and support advisors on a deeper level so that they can handle customer expectations with greater ease. This could be a critical evolution as the consumer world grows more focused on the concept of customer experience.
The opportunity to spot trending patterns in customer sentiment and behaviour could also help call centre leaders to create training strategies that support their future campaigns, improving ROI, and resource planning.
Improving Analytics with AI
Ultimately, AI, chatbots, and the rise of machine learning in the call centre could allow companies to capture a great deal of information related to customer interactions. This information can help to optimise the contact centre process and ensure that businesses can spot things like dissatisfaction or anger in large sets of data. The good news is that most experts don’t believe that AI is set to overtake human insight in the contact centre just yet.
9 out of 10 people still say that there should always be an option to transfer their call to a live person. The AI input simply makes analytics and customer care easier to maintain. We could be moving towards the perfect blend of man and machine in the CX journey.