In my first post on this topic, I covered at a high level the basics of how speech analytics can bring deeper customer engagement to the contact center. In this follow-up, we’ll look at why the industry is starting to take notice.
A lot of the industry interest in speech analytics is being driven by a heightened focus on the customer experience. In today’s hyper-competitive economy where there the meager opportunity for product differentiation and operational efficiency has been squeezed as much as possible, customer experience, driven by customer service, has emerged as a primary area of differentiation. There is a realization that a lot of learning is needed to before an organization is ready to deliver differentiated customer service. Organizations are looking at their existing data such a recording
that they already have, to see if they can extrapolate more value out it and turn it into a true enterprise asset.
Customer interactions are becoming increasingly complex. With so many customers seeking self-service routes before they engage with the enterprise, agent-customer phone interactions are more complex than they used to be. Because of this, organizations are trying to figure out if they can better understand those interactions, some of which are using speech analytics to do so.
Customers have changed. They are more connected, they are more informed, and due in part to the increasing use of social media, they have a voice like they never did before. And while the customers have changed, what they want from their service provider has changed as well. Speech analytics can help an organization get a quantified view into those changes.
At the same time, technology has evolved such that the actual recordings are easier and cheaper to capture and store. Unified communication has contributed to that by reducing the reliance on hardware and shifting it to software which, due to falling storage costs, is easier to configure and maintain. And speech analytics options have also increased such as text-to-speech and even phonetic-based approaches. Plus, speech analytics solutions are increasingly more open, enabling data to be extracted and integrated easier than in the past.
In some ways, it’s a perfect conversational storm: the drive for service differentiation, the need to understand the new customer and their new needs, and technology evolution.
Tim