Take Control of the Future of Your CX
In a world of rising customer expectations and ever-expanding, ever-transparent digital touch points, it’s clear that no company can afford to slack on their customer experience (CX) approach. It’s all too easy for the modern user to publicly call out a brand’s poor CX online on social channels, and in many cases, switching to a competitive vendor is a virtually frictionless experience. In the face of such challenges, how can leadership ensure their CX strategy remains effective, competitive and relevant?
In addition to mastering the basic fundamentals of customer service, all CX experts will agree that a technology-driven approach is an absolute must. Brands that are winning at the CX game are utilizing all kinds of tools to meet the newfound demands of their customers. This includes leveraging big data to personalize the user experience, implementing advanced monitoring systems to proactively detect issues or problems, and expanding their use of alternatives to traditional phone support in the form of self-service options and chatbots.
A key issue, however, is that business leaders may not always know how to approach the implementation of a new technology project to enhance CX. A study from Forrester, for example, demonstrated that while 72 percent of businesses say improving customer experience is a top priority, only 63 percent of marketers prioritize implementing technology investments that will help them reach this goal. This shouldn’t come as a big surprise —oftentimes, the technologies being harnessed to improve CX can seem complicated or intimidating.
Take artificial intelligence and machine learning, for instance, which many companies choose to adopt for a wide range of business applications, including within the call center. These terms can bring to mind a giant black box of complex algorithms and obscure programming languages, and can mystify even the savviest of business leaders.
For the CX leader, in particular, implementing AI and ML represents a pretty big leap from the decades spent practicing “traditional” customer service. It’s a major transition, both technically and psychologically speaking, to move from a room full of call center agents to a software system. And most of the time, this software is either created by a third party or an internal engineering team — neither of which is likely to be steeped in the domain expertise necessary to deliver world-class CX.
It’s therefore no surprise that business leaders are reticent to outsource CX. The good news, though, is that a new breed of solutions is emerging. These approaches are founded on the understanding that the best results don’t solely rely on either technology or the CX leader, but optimizes the two to work together. Companies are thus able to harness bleeding-edge technology while keeping CX leaders in the driver’s seat to orchestrate and customize the experience.
From intelligent virtual assistance to self-serve FAQ to escalated agent assistance, CX experts can design full dialog workflows and create multi-task, multi-initiative natural language conversations at scale, for virtually any use case. They even have the ability to pilot and test certain components before transitioning them to live scenarios, making it possible to safely experiment and test the effectiveness of new approaches.
The best part is that you can have all of these capabilities without needing to interact with or configure any of the backend technology. The AI simply powers all of this behind the scenes, working in the background as the means to an end.
The new standard for CX will be AI-powered solutions that keep the CX leader in complete control of the experience, and confer an unprecedented level of flexibility, transparency, and adaptability. This will be critical in helping CX professionals feel emboldened by the possibilities of artificial intelligence, view technology as a partner in crime, and retain a human touch in the customer experience process.
About the Author
Yi Zhang is a co-founder of Rul.ai, focusing on AI technologies. She has been a consultant or technical adviser for several large companies and startups.
She is also a Professor in School of Engineering, University of California, Santa Cruz. Her research interests are personalized search and recommendation, natural language processing, machine learning, data mining and computational economics. She has received various awards, including ACM SIGIR Best Paper Award, National Science Foundation Faculty Career Award, Air Force Young Investigator Award, Google (News - Alert) Research Award, Microsoft Research Award, and IBM Research Fellowship. She has served as program chair, area chair and PC member for various top tier conferences. She was an associate editor for ACM Transaction on Information Systems. Dr. Zhang received her Ph.D. and M.S. from School of Computer Science at Carnegie Mellon University and her B.S. from Tsinghua University.