Conversational AI and Customer Engagement – What are the experts saying?

March 28, 2019

Customer experience is more important than ever. Modern customers dictate why, when, and how they would like to engage with a brand, and companies are looking for innovative ways to elevate their experience. Naturally, they are exploring the potential of conversational AI and its promise of transforming the customer experience.

Recently, I attended two highly informative conferences which looked at AI technologies and their impact on customer engagement – the Conversational Interaction Conference hosted by AVIOS in San Jose and Enterprise Connect conference in Florida. Both conferences had dedicated tracks on Conversational AI and the contact center and were attended by analysts, technologists, vendors and industry practitioners.

In the sessions that I attended, these key themes stood out as defining trends in the customer engagement market.

1 in 4 contact centers could be fully automated in 5 years
Ovum, the leading research and consulting firm, predicts that over the next 5 years 25-35% of contact center interactions could be fully automated and handled without the involvement of a live agent. However, in order for this to happen, companies need to be diligent in deploying conversational AI in the contact center. Done well, conversational AI will efficiently handle customer service requests, avoid long hold time, and customer frustrations.

Industry practitioners agree that AI in the contact center can help consumers resolve many mundane tasks (such as password resets, account management, payment updates, order status, etc.) in a highly conversational manner, without the need of interacting with a human. And when the automation does not have an answer, it is agreed among leaders in contact centers that escalating to a human agent, while maintaining a historical context of what has already been accomplished, is necessary to deliver a satisfactory outcome.

Embedding AI into customer service will reduce OPEX
In a recent report, Gartner stated that by 2025, customer service organizations that embed AI in their multichannel customer engagement platform will elevate operational efficiency by 25%. This is what enterprises are looking for– efficiency while reducing operational costs.

Today, there are hundreds of vendors claiming to offer AI-driven solutions for customer care. Yet, a recent study in Europe MMC Ventures found that 40% of “AI startups” don’t actually use AI. With the growing frenzy around the digital transformation sector, AI has become a catch-all phrase that’s often used flippantly. This confusion leads to the impression that anyone can deploy an AI solution for customer care, but the reality is, it’s not that simple. Complex customer care transactions require the expertise to build a solution that truly understands the customer’s intent.

Look for a partner that can demonstrate the strength of their technology stack, not with a fancy demonstration but will real use case results. Ask the vendor to define AI and ML, and then to demonstrate how the product uses AI. Make sure you understand how their solution reduces OPEX without sacrificing CSAT and customer experience.

Don’t make me speak robot
One of the main underlying themes for both conferences was around customer expectations and preferences. People want ease when seeking answers from brands. However, 69% of consumers state it is difficult to navigate an automated system to resolve a customer service issue.

One of the keys to successfully automating customer service, whether via voice or digital channels, is to let customers describe their issues in their own words, rather than feeling that they have to use specific terms or “speak robot”. DMG-research found that self-service is the method of choice for all generations, as long as the solutions work well.

Advanced software learns from past interactions and improves responses over time
Most of the conference attendees agreed that today’s AI still needs a lot of training and tuning. A lot of automation fails because it does not understand the intent that the user is trying to accomplish. To take on any level of complexity an AI solution needs constant TLC.

“For AI to become accurate, it needs a large set of training data,” says Alan Lepofsky, VP and Principal Analyst of Constellation Research. “For things like cat pictures, that’s easy. For making business decisions, especially personal ones, it’s harder.”

Technology is not perfect, and often needs the assistance of humans to ensure accuracy. At its core, AI is a set of mathematical equations and algorithms that require human training. This means that AI, and machine learning, are only as smart as we teach them to be. When applied properly, AI is a perfect assistant to help humans become more productive. Technology is not here to overcome us and overpower us, but rather assist us and improve our quality of life.

The road to omnichannel needs to scale
Although the move towards omnichannel, or the ability to switch channels while maintaining context and personalization contact centers, is an ongoing trend, progress has been slower than anticipated. In today’s contact center many channels are siloed, making it difficult for the customer to start a conversation in one channel and continue it in another. According to Forrester’s 2019 predictions, only 40% of chatbots will have an effective path to a live agent.

Omnichannel is a prerequisite for a great customer experience. The first step is to connect your channels. Today companies often have separate managers overseeing each channel. For example, the contact center, website, and social media all have different managers. A company that wants to create an omnichannel solution should consider having a Customer Experience manager who oversees all the channels and establishes a framework to connect them together. This sends a clear message that the brand cares about customer experience.

According to research by the Aberdeen Group, companies with strong omnichannel customer engagement retain an average 89% of their customers, compared to just 33% for those companies without. Driving self-service options across all channels will provide your customers the ease they want to get their tasks completed while ensuring that they receive a consistent brand experience. It is equally important to make certain that all self-service channels can scale to incoming volumes, so during the busy season or if there is a promotion, customers are able to get the information they need without any delay.

The conferences gave me a lot to think about, and reinforced my belief in the potential of conversational AI. If I had to choose one takeaway for companies wanting to implement Conversational AI, it would be this: It all starts with finding the right partner. Understand that AI is powerful but not sufficient if not trained and tuned regularly. Taking the time to develop and deploy a well-designed solution will result in better customer experience by reducing resolution times while increasing CSAT. And when AI can’t resolve the task, a warm hand-off to a live agent is needed. Over time, with the help of humans, AI will learn and improve customer self-service rates.

Next week, Interactions will be at The WSJ Pro AI Executive Forum. Jim Freeze, Interactions’ Chief Marketing Officer, will present with Damon Kowolewski, Vice President Americas’ Customer Solutions Transformation at MetLife. The presentation, “Conversational AI Case Studies– Elevating Customer Experience While Materially Reducing Costs” will take place at 12:45 p.m. EST on Tuesday April, 2nd.

Tractica

Whitepaper

Why Conversational AI Is Key to Customer Service in the Customer Experience Era

Learn More

Want to learn more? Let’s talk.