How AI is Changing Customer Service

AI is slowly becoming a part of the way we do business in the digital and data-driven world is understood. Without AI, companies, especially those aiming to implement more engaging customer care, may feel challenged with the mounds of customer data being generated. Rick Britt, VP of Artificial Intelligence at CallMiner, the AI-based customer engagement and speech analytics solution, shares latest data and research findings through the infographic ‘The Role of AI in Customer Experience’ to highlight how people are already interacting with the technology even without realizing it in an attempt to allay the fears of what lies ahead

To define Artificial Intelligence (AI), it’s best to understand that the term is used to describe a great many things. The idea of AI as people currently view it has been around since the 1950s, but it’s recently taken on a much more involved and transformative form due to advancements in computing, more specifically computational mathematics.

The building block of AI is data. When it comes to customer service, the underlying data sets can be massive and complex, making them very difficult to understand using traditional methods. In order to harness AI for improved customer service, you need to have a good handle on the data available from customer interactions.

Advanced analytics solutions are intended to uncover the Holy Grail of customer service data: the interaction a customer has with your brand in the contact center. By transcribing the recorded audio of an interaction between customer service agents and customers, it becomes searchable categorized text which can be appended with relevant metadata. The result is an incredible amount of information that benefits from a form of machine intelligence like a neural net to map and make sense of the data.

Ways machines become smarter

This is where AI comes in. A first step is to structure the data by appending the contextual categories or clusters to the transcript. This adds a level of relevance and context that words alone do not reliably carry. Performing such curation only maps around a third of the data, the remainder requires advanced techniques. The remaining data is mapped within a semantic network using technology such as natural language processing (NLP) that can automatically categorize data based on relevant phrases, acoustics and characteristics.

Application of machine learning tools are the next step. Technology can look at the mass of unstructured data and uncover trends or patterns that are not easily visible and start to answer thorny questions such as, “Why are consumers canceling a newly-launched product?” or “Why do certain customers have a higher likelihood of taking a certain valuable action over others?” These types of insights allow customer care and customer experience managers to react in entirely new ways, so they can proactively optimize or re-imagine the experience behind the scenes. This opens the possibility of fulfilling needs that customers didn’t even know existed. Additionally, AI can also be used for speech analytics to improve agent performance. Uncovering these nearly hidden patterns and trends that are hidden to human eyes is the core power of AI in customer care.