Exceptional customer service is key to winning and retaining loyal customers. Emerging technologies and evolving customer expectations in the digital age are disrupting how traditional contact centers operate and challenging how organizations deliver service to their customers.
We synced up with Craig Le Clair, Vice President, Principal Analyst at Forrester, to get his perspective on five of our burning questions around the intersect of technology and the impact on customer service. Craig Le Clair is an internationally recognized expert in helping companies transform, covering areas of robotic process automation, dynamic case management, AI solutions, customer communication, and other disruptive technologies.
As organizations are on the cusp of transforming business strategy to deliver top-notch customer experience, this must-read Q&A highlights important concepts to consider. AndÖ Craig's answers may just surprise you!
Tackling Complexity Challenges with Dynamic Case Management
Appian: Why does Case Management continue to be central to effective customer service?
Le Clair: The simple tasks are being automated rapidly and handled self service via chatbots or the customer website. This means that the calls that now come in to the contact center are more likely to be harder and complex exceptions, that a Dynamic Case Management (DCM) solution handles well. Processing of submissions and claims of all kinds customer onboarding, loan origination, healthcare, and customer inquiry responses fits into the wide range of customer-facing situations where DCM applies. For example, imagine a letter from a recently divorced bank customer. He wants a change of address so that he can close the joint bank account, set up two college trust funds for his children, and transfer pension funds. Of course, the bank wants to deal with the customer request as efficiently and effectively as possible, but it also needs to consider regulations for example, the pension rights might be subject to final adjudication by a court.
Instead of treating all work items the same way by routing them down the same preordained path, DCM recognizes that complex work takes many different paths based on the situation at any given time. DCM also empowers customer service agents to complete more of the work assignment themselves rather than carving work into lots of discrete parts.
Clearly, the organization would not have a standard process definition to deal with an increasing number of multifaceted customer requests. Traditional Business Process Management (BPM) would involve creating a separate work item for each aspect of the issue. On the other hand, a DCM approach would involve treating the customer requirement as a single request with a link into needed repositories and a dynamically created set of tasks based on the context. The customer service representative would dynamically bind simple processes some of which might be triggered automatically to handle each facet of that request.
Start with Employees for AI-based Chatbot Adoption
Appian: How is intelligent automation including AI disrupting the agent and customer experience?
Le Clair: As of today, there has been only moderate disruption. Adoption of chatbots are an example. They are the emerging user interface particularly for the younger set. Drop-downs, search screens, and clever navigations aren't necessary for many machine interactions. In fact, they can get in the way. Millennials simply want to text a question and get an answer.They don't really want to download a clumsy mobile app. Crisp text messaging without precise spelling and construction, using NLP and natural language generation (NLG), is the preferred interaction for Millennials. Hint: Older generations may prefer it, too!
Chatbot's future in the contact center is secure, but they are not quite ready. A major telco is handling 6 million requests a month with chatbots, but these are assisted by humans in the background not autonomous. Let's look at autonomous AI-based chatbot adoption. It's not good. Chatbot success rate for areas like customer service is low, with some early adopters pulling back. Facebook scaled back AI after chatbots hit a 70% failure rate. Why the high rate of failure? Chatbots aren't sophisticated enough to hold up their end of a social relationship. They can be boring, lose context over time, repeat themselves, or respond to keywords only. Let's face it. Humans today just don't have patience.
But why is this surprising? Why do we expect a machine to be as adept as humans at communication? Early humans that couldn't distinguish a friend from a foe didn't evolve as rapidly as those that could. Humans evolved to communicate with each other with verbal and nonverbal nuances that follow complex rules. These advanced ways, despite Alexa in your kitchen and AI excitement, are difficult to program into a computer today. Machines today stumble at human interaction. Their ability to act human is overstated in the general media and leads to an unrealistic expectation for AI.
It will be four or five years before humans can reliably converse with machines. Businesses realizing this are investing in chatbots that interact with employees first. They recognize that a "centaur-based approach," is best today, one that allows humans to do what humans do best, and let machines show their talents.
Productivity Gains with Robotic Process Automation
Appian: How specifically is RPA transforming operations and customer processes?
Le Clair: Robotic Process Automation (RPA) for agent support is helping. In this case, called "attended mode" in RPA speak, an agent can initiate a Bot from their desktop. The Bot can create a document and send a document to a customer, take care of updates to CRM systems, order something for a customer, or update a back-end financial system. As shown below, RPA is providing a 0.4 to 1.2 productivity enhancement to the contact center.
Mapping to Customer Journey Key to Omni-Channel
Appian: What does it mean to have an omni-channel environment versus multi-channel support? What is the impact on engagement?
Le Clair: Multi-channel is simply giving your customer several channels to use such as voice, web, e-mail, text, and perhaps a chat interface. Omni-channel implies understanding the context of the customer, what they are trying to accomplish. It requires absorbing information across the channels and mapping it to the customer journey. In this way, an enterprise can understand the customer goals and create a more useful and enjoyable outcome. The simple chart below explains the difference.
Agile Platform is the Foundation
Appian: Why is it important for a platform to combine customer engagement, case management, and intelligent automation to deliver effective customer experience?
Le Clair: Tying these elements together in one platform allows organizations to quickly build and deploy contact center software that can handle the increased complexity of service requests, incident management, and investigative work. With a more agile layer that unifies data from existing systems, automates repetitive work, and optimizes processes, organizations have a better understanding of customer context that can be used to drive action. This transforms how organizations engage with customers, enabling increased personalization, faster resolution, and a seamless customer experience.
Redefining Customer Engagement
Omni-channel communication, intelligent automation, artificial intelligence (AI), and case management are merging to forever change how organizations service their customers.
For more insight on how the confluence of these technologies are redefining enterprise operations and transforming the customer experience, view the on-demand webinar The New Reality for Customer Engagement with featured speaker Craig Le Clair.
Jenna Harvey
Industry Marketing Manager
