Robotics is nothing new to some aspects of manufacturing and the IT industry, but it is relatively new in the customer experience (CX) market. The term often conjures up images of little gray machines taking over tasks previously handled by humans – machines making cars, programmed vacuum cleaners and the like. In the CX space, however, we are not talking about machines but about software that can automate routine tasks. For the time being, I don’t believe robots will take over the contact center and replace human agents. Indeed our recent research into next-generation contact centers in the cloud strongly suggests the opposite. It shows that the telephone is still the top channel of communication and that almost two-thirds (62%) of organizations expect call volumes to rise over the next 24 months. Thus agents will continue to handle large volumes of interactions, which may become more complex.
Topics: Customer Analytics, Customer Engagement, Customer Experience, Speech Analytics, Employee Engagement, Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
Analysts have been talking and writing about a “360 degree” view of the customer for years. Our own benchmark research into customer relationship management shows that only37 percent of organizations are able to produce analysis and reports that yield such a comprehensive view. Other research into next-generation customer analytics reveals that the main issue in this area for nearly two-thirds (63%) of organizations is data availability. To make the situation worse, customer-related data is getting ever more numerous and complex. A principal reason for this growth is the number of communication channels consumers now use to engage with organizations and the type of data these channels produce. It includes call recordings, text messages, email, social media posts, customer feedback surveys, chat scripts and event data such as videos that users download. All of these types of data are unstructured , which makes them harder for conventional analytics tools to access and analyze.
Topics: Customer Analytics, Customer Engagement, Customer Experience, Employee Engagement, Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
In the late 1990s, CRM systems were launched to help organizations become customer-centric, to manage customer relationships from end to end, through marketing to sales to customer service, and to provide a “360-degree view of the customer.” For a variety of reasons (overselling, lack of proper adoption, missing functionality), they never lived up to many companies’ expectations, and so CRM got a poor reputation. I recently wrote that customer experience management has undergone significant change in the last 18 months, taking over the role of helping organizations become customer-centric, and that CRM vendors have played a part in these changes. Some of the larger ones have, in my view, taken a backward step by breaking CRM into three components to support marketing, sales and customer service; this makes it harder to support the end-to-end customer life cycle.
During a recent briefing with NGData, I was initially put off by excessive “marketing speak.” The team began by describing its product, Lily Enterprise, as a “customer experience operating system.” Being used to having operating systems run entire computers, I wasn’t sure what this meant. This term was followed by a statement that NGData’s products help companies transition from being “B2C to C2B,” that is, to put the customer first, an idea that has been around for several years but in my experience few companies achieve. One of the biggest challenges in this regard is that most companies are organized into business groups, and each business group typically has its own processes, systems and metrics, a situation that makes it hard to have a single view of the customer and take actions based on the same customer view, and which lends itself to focusing on internal goals, not the customer. As an example, our research into next-generation customer engagement shows three key impediments to delivering exceptional customer experiences: systems that are not integrated (for 49% of organizations), communication channels managed as silos (47%) and customers receiving inconsistent responses at different touch points. The root cause of all these is data – customer data. Organizations have multiple systems that generate customer data, in multiple forms: for example, structured data in CRM and ERP systems, voice recordings, text data from multiple sources (letters, email, Web scripts, text messages, chat scripts and social media posts), video and event data such as a customer downloading a film. With so much data in so many formats, it is hard for companies to generate a single, “360 degree” view of the customer that can be shared across the whole organization.
Topics: Customer Analytics, Customer Engagement, Customer Experience, Speech Analytics, Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics