Keith Dawson's Analyst Perspectives

Conversational automation is one of those software segments that means something different depending on who you are or your role in an organization. According to my colleague Jeff Orr, the core of the idea is that conversational automation tools benefit from artificial intelligence (AI), allowing software agents, chatbots and virtual assistants to automate customer interactions and internal processes. This broad definition hits the mark, I think, because it identifies the core functions without...

Most of the discussion and planning around artificial intelligence (AI) tools for contact centers and CX has focused on finding appropriate use cases and understanding how to deploy these tools. There are already plenty of success stories about enterprises reducing friction for agents, saving time and expanding the breadth of interactions that can be handled automatically.

It is unfortunate that business-focused digital communications are sold under three different headings: Contact Center as a Service (CCaaS), Unified Communication as a Service (UCaaS) and Communication Platform as a Service (CPaaS). (And that just counts the cloud options—let us acknowledge the huge, continuing, installed base on premises.) These are terrible ways to describe complex, varied and overlapping offerings. What distinguishes them are:

Self-service has changed immensely in recent years. It has gotten better, qualitatively, in delivering answers and resolutions to customers. But it has also gotten extremely complex, relying on a basket of new technologies to achieve results. It helps to look at it through the eyes of the three main constituencies that are affected by it: customers, contact centers and the businesses they sit in.

Verint held its analyst conference recently, using the opportunity to flesh out how it is responding to the rapid developments in artificial intelligence (AI) and data-related technologies and to changes in the way enterprises consider the purchasing process for contact center-related tools. 

The first wave of discussions around artificial intelligence (AI) in the contact center was focused on providing software buyers with a general understanding of what the technology could do. Now the conversations are becoming more specific, focused and direct. Buyers are more aware of the spectrum of available use cases and appear to be exploring how to map new tools to the particular business problems they face. Contact center buyers are approaching new technology deployments (or enhancements...

We are going through an analytics revolution in and around contact centers. There is more data to analyze and better tools to conduct the analysis. One important advancement is assessing customer sentiment and using it to predict (and influence) behavior. Enterprises are using customer experience programs to identify and act upon hidden "moments of leverage" where customers may be inclined or primed to make a purchase. To do that effectively, enterprises need insight into how the customer...

The speed of innovation and transformation has picked up considerably in the 2020s, thanks to the confluence of artificial intelligence (AI), cloud computing and the pandemic. Modern consumers have wildly different expectations than their predecessors when it comes to service delivery, whether that means a preference for digital channels and self-service or a willingness to do their own troubleshooting and research. As a result, buying an operating platform for a contact center is not a simple...

The pandemic laid bare the tenuous relationship between many contact centers and their agents. The abrupt shift to remote work was just one component of the changes still under way. The past four years have also seen enterprises reckoning with questions about how to hire, what to pay their employees, what skills are needed and how an avalanche of new technology will change their operations. 

It often takes longer to adopt new technology in the customer service delivery environment than in other business areas. In fact, service operations are among the most efficient and well-organized processes (despite what consumers might think). Because both the processes and the technology that drive them are deeply engrained in many companies, many people resist large-scale transformation projects because of their disruption and the uncertainty of outcomes.