Chatbots in the Contact Center, Part 1: Common Applications and Misconceptions

FROM THE MARCH 2019 ISSUE

Chatbots in the Contact Center
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With consumers increasingly expecting anywhere, anytime access to conduct simple transactions, more businesses are deploying chatbots to handle routine and repetitive customer service tasks. Automation has enormous appeal as an efficient, affordable option for companies that lack the human staff to effectively manage the workload in the contact center (one of the top 3 challenges cited by participants in our recent Challenges and Priorities survey).

As the technology continues to evolve with advancements in natural language, AI and machine learning capabilities, the chatbot experience is becoming more human-like and increasingly popular among consumers. Although Gartner had predicted that, by 2020, the average person would likely have more conversations each day with chatbots than their spouses (hello, Alexa), it doesn’t mean that chatbots will be replacing humans in the contact center, but rather working alongside agents to assist and enhance service delivery.

To gain a better understanding of chatbot applications in the contact center, we reached out to chatbot solutions providers for their views on current usage, developments and advice for successful deployment and use. Our experts for this Q&A series are: Chris Connolly, Vice President Product Marketing, Genesys; Emma Furlong, Lead Content Strategist, Clinc; Dave Hoekstra, WFM Evangelist, Teleopti; Scott Kolman, VP of Product & Corporate Marketing, Five9; Alok Kulkarni, CEO, Cyara; Jen Snell, VP of Product Marketing for Intelligent Self-Service, Verint; Shellie Vornhagen, SVP Marketing and North American Sales, Astute; and Charly Walther, VP of Product and Growth, Gengo.ai.

In Part 1 of this series, our experts offer their thoughts on common uses for chatbots in the contact center, and clear up some misconceptions about chatbot capabilities.


What are the most common applications/uses for chatbot technology in contact centers today?

CHRIS CONNOLLY: Our customers are primarily using chatbots on owned digital channels, such as web and asynchronous messaging, to determine customer intent and, when appropriate, deliver the interaction to a suitable agent. Our findings show that 60% to 70% of web interactions that engage with a bot are contained within this experience.

EMMA FURLONG: The main focus of chatbot technology in the call center today is focused around replacing IVR systems. IVRs are traditionally the biggest pain point for customers seeking fast service or quick issue resolution.

JEN SNELL: The most common applications of chatbots and IVAs are to assist in self-service efforts and alleviate contact centers from high-volume, tier-1 interactions.

SHELLIE VORNHAGEN: Many companies approach chatbots as the next iteration of a website FAQ, enabling customers to easily find answers to common questions. Some view them as a replacement for contact forms, letting customers contact companies without needing to hunt all over the website. A great chatbot will deflect most tier-1 customer questions and issues, be available across multiple communication channels (site, app, SMS, Facebook Messenger, etc.), and enable easy escalation to a live agent when needed. This addresses consumers’ expectations for instant, omnichannel support while allowing contact center agents to focus only on the cases where a human touch is truly needed.


What is the biggest misconception that business leaders have about chatbot capabilities?

CHRIS CONNOLLY: The largest misconception that business leaders have about chatbot capabilities is that a stand-alone chatbot is enough to provide superior customer service. Following this misconception are smaller misconceptions regarding the effort it takes to deploy a well-functioning bot. In the first instance, we have found that CX leaders find it necessary to connect the bot experience seamlessly with the human experience. On the other hand, companies that are simply seeking to “tick the box” on chatbot often rely on upfront stand-alone bot experiences with little to no connection with the contact center—leaving customers with a broken journey that ultimately leads to further frustration and damages brand perception.

We have also found that many customers we engage with believe they either need highly specialized skills to deploy a chatbot, such as that of a data scientist, or on the opposite end of the spectrum, that IT can do it with existing talent. In our experience, the answer lies somewhere in the middle—technology has matured to the point where specialist skills are no longer required, i.e. you don’t need a Ph.D. However, the effort required to satisfactorily maintain a working bot is also understated. We have found that many IT departments that do not understand user interface design have attempted to deploy bots only to be left with an end-user experience that is, well, robotic. Similarly, we’ve seen CX leaders identify new roles, such as “bot content curator,” which are charged with ensuring consistency of persona and experience delivered by the bot, drawing a parallel with Voice User Interface Designers (VUIs).

EMMA FURLONG: I think the biggest misconception around chatbot capabilities is that chatbots can’t handle context or messy human language. While many chat solutions do struggle with this, it doesn’t mean that the technology doesn’t exist. Clinc’s conversational AI was born out of a research lab at The University of Michigan which innovated on several key problems in the field, context among them, to see if it was possible to create an authentically human experience with AI. This research endeavor uncovered new approaches that make things like contextual awareness, conversational healing and the comprehension of messy language possible, and we’ve already deployed chatbots with those advancements in the market today. The technology is out there, you just need to know what to look for.

DAVE HOEKSTRA: The biggest misconception is that chatbots will eliminate the need for skilled workers. When chatbot technology matures, it will be able to automate repetitive tasks and foster better customer experiences than IVRs and other self-service technology have done in the past. Yet the ability for a human to empathize and make decisions in a “gray area” is nearly impossible to replicate. In fact, the growth of chatbot implementations is instead placing a greater focus on the frontline employee and their competence. With chatbots taking on more of the mundane, automatable tasks, employees are instead presented with more complex cases that require emotional intelligence and a higher level of skill to bring customers the solutions they need. Emotional intelligence and problem-solving skills are particularly needed in the case of “bot-failure,” when a customer doesn’t get their question resolved by the bot and is transferred to a human agent. Then companies need to make sure they have knowledgeable, empathic employees available to turn customer disappointment into a positive experience.

SCOTT KOLMAN: Probably that it is the panacea of all interactions. Like any other interaction channel, it is important to understand and assess what types of customer issues are best served over that channel, as well as what customers expect to accomplish.

JEN SNELL: One of the biggest misconceptions is that all chatbots are created equal and will easily deliver value for your business.

Enterprises are inherently complex, and when you’re truly looking to solve real business problems or achieve goals with this technology, it’s never just a matter of building a brain and plugging in an API. It’s a matter of integration with systems of record, continuous improvement and evolution of language models, designing and deploying to deliver measurable ROI to the business, along with the ability to extend and grow with ease overtime, and so much more.

SHELLIE VORNHAGEN: A common misconception about service chatbots is that you will need to author every response the bot can give. But advanced bot solutions can take into account any existing content you may have, like knowledgebase articles or FAQs, as well as gather information via integrations into other systems or websites.

Another misconception we see with digital self-service in general is an attitude of “set it and forget it.” While some chatbots can automatically learn and improve based on what your live agents do, you will also need to regularly review reports that show what gaps exist in the bot’s knowledge. And since products and policies tend to change, having an easy, non-technical tool to update content is absolutely necessary.

Lastly, some companies make the mistake of launching a chatbot without an in-channel escalation path to a live agent. If a customer has chosen to interact with you over a website chatbot or via Facebook Messenger, they want to stay in that channel even if further help is needed—and they definitely don’t want to repeat what they just told the bot! Make sure that immediate, in-channel escalation is available at any point during self-service interactions, and that agents are given all the context of the interaction when assigned the case.

Read Part 2 of this series for insights about how chatbots can be used internally to support agents, and usefule advice on how to prepare for chatbot adoption.

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