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How AI Can Reduce Friction Across the Customer Journey

Contributed article by Mark Eichten, Executive Director, Voice & AI Bot Professional Services, TTEC Digital 

When we think about the customer experiences that really matter, we often focus on face-to-face interactions. But in today’s increasingly digital world, the customer experiences that take place on digital channels are just as important. In these channels, it’s not about creating exceptional experiences, it’s about creating effortless experiences – the experiences where customers can meet their needs without friction.

Unfortunately, digital channels are often anything but frictionless. Interactive voice response (IVR) systems force us to listen to endless array of options. Chatbots don’t understand what we’re trying to communicate. And speaking to a human agent can mean waiting on hold for hours.

Fortunately, we can improve these areas of customer friction with artificial intelligence (AI). The key is to apply AI intelligently throughout the customer journey, and that requires a strong foundation in CX (customer experience) principles as well as a deep understanding of the technology. The following are three common CX challenges that AI can help alleviate.

AI can fix frustrating IVR systems

Traditional IVR (interactive voice response) systems follow a pre-determined sequence, so they can’t respond intelligently to customer requests. This leads to frustration as customers listen to an endless array of options never to hear the reason they’re actually calling.

Today’s customers want to self-serve and quickly resolve problems without human intervention. Unfortunately, because of design shortcomings, the IVR system often leads customers to want to speak with a person who might be able to resolve their problem.

With conversational AI, businesses can improve their IVR systems. An AI-enabled IVR, or intelligent virtual agent, can more quickly and accurately help customers resolve issues without human involvement. Conversational AI built with Natural Language Understanding (NLU), Natural Language Processing (NLP) and generative AI can interpret customer inquiries, even if they’re spoken in a conversational tone. IVR systems embedded with AI can also simplify their menu of options. Instead of including a prompt for a laundry list of questions, the customer can state their problem and the IVR will give them the correct response or route them to an agent. Even better, some AI-powered IVR systems use advanced analytics to predict the question before the customer even asks it.

AI can make chatbots more helpful

Traditional chatbots are designed based on a set of rules, which can make conversing with them frustrating. When a customer asks a question, the bot searches for the right rule, and responds with a scripted reply based on a set of known keywords – and that often leads to friction because the answer is wrong or simply irrelevant.

Chatbots powered by conversational AI aren’t limited by keywords or rules. Instead, they use data, machine learning (ML), NLU and NLP to recognize speech and text inputs. This helps the bots understand and interpret the nuances of human language and engage in more natural and fluid conversations with customers.

These newer chatbots can also identify common user issues and proactively provide solutions, resulting in a more helpful user experience. These chatbots can even access past interactions and use that historical information to offer personalized recommendations and responses.

AI can help improve the agent experience

Agents tasked with responding to frustrated customers experience a great deal of stress, and compounding that stress is the fact that agents often lack the tools they need to quickly solve customer problems.  

While AI can’t eliminate all agent stressors, it can help alleviate some of them by making workloads more manageable and giving agents the tools they need for success. If a business is already using conversational AI to improve IVR and chatbots, they will greatly reduce call volumes by making it easier for customers to problem-solve. AI can also help predict peak call times so that businesses can staff contact centers appropriately to meet high demand.

AI can also give agents the assistive tools they need with interactive knowledge centers that draw on knowledge bases, manuals, and FAQs to deliver answers to agents via tools in their contact center technology. In addition, automatic conversation summarization can replace tedious post-call work.

Next steps for AI in your customer experience strategy

Improving IVRs and chatbots and improving the agent experience are really just the beginning when it comes to what AI can do to reduce friction in the customer journey. You can apply AI to many interactions, but you must be strategic about how you do it so that you don’t inadvertently increase friction. If you’d like to explore your readiness to use AI in your customer experience, take this 10-question readiness assessment.

 

Mark Eichten is executive director, voice, and AI bot professional services, at TTEC Digital, a global leader in customer experience orchestration, combining technology and empathy at the point of conversation. With decades of innovation experience across the world’s leading contact center technology platforms – plus in-house expertise in CX strategy, data and analytics, AI and more, TTEC Digital delivers an unmatched skillset for organizations looking to forge deeper customer relationships and drive better business outcomes.