A featured contribution from Leadership Perspectives, a curated forum for enterprise technology leaders, nominated by our subscribers and vetted by the CIOApplications Editorial Board.
Voicing the Future of Customer Service
There a couple of trends that we think will play prominent roles. First among them is that customer support is emerging as the primary use case for that technology, in the form of AI-powered virtual agents (whether for chat or voice). Even though everyone agrees that customer satisfaction is the key to business success and that the contact center is a strategic asset, the lack of budget or trained customer support representatives to provide nonqueued service 24x7 usually makes that goal very hard to achieve. So, most companies are turning toward automating customer support functions in some way.
Web self-service is a popular way to do that, but it only solves part of the problem because many customers, especially older ones, prefer using the telephone. For servicing those customers around the clock, an AI-powered, voice-based virtual agent, also known as conversational IVR (for Interactive Voice Response), is a promising alternative.
The other trend is the rapid consumer adoption of smart speakers, like Google Home and Amazon Alexa, which are basically just delivery mechanisms for virtual assistants. As adoption continues, we think voice will eventually become the standard for human-machine interaction in all kinds of settings.
Please elaborate on the challenges that organizations will need to address related to the Virtual Agent technology space.
Building a virtual agent is not an easy task. Undeniably, companies have a lot of experience in building websites and apps, but building bots and virtual agents is a different animal. For example, the design process for bots is much more open-ended; most companies have no idea how many different ways customers will phrase questions nor the best responses for them, and that’s a major challenge. Often, companies start by simply adding a chat channel to their website because that seems easier. But even developing chat apps is different than building bots; the tools for the latter are newer and not as mature as they are for messaging apps.
What are the major tasks for organizational CIOs at this point in time? Is there any unmet need in terms of this space that is yet to be leveraged from the vendors?
The major task for CIOs at this time is to develop some vision about how AI-powered agents can improve customer experiences for their company. I saw some new research recently that supported the idea that quality of customer service, not products or price, is or will soon be the main competitive differentiator for brands of all types and sizes.
Companies, as mentioned, should also work on voice experiences troubleshooting through automation and only when they can’t do that, they should hand it off to support agents
The old way of doing things, with armies of live agents and an entire forest of phone trees, isn’t going to cut it anymore; customer service virtual agents need to have a major role in augmenting human agents.
On that point, I think there are two gaps in the marketplace today. One is that there aren’t a lot of tools for rapid development available (Google’s Dialogflow is one); and most can’t tell you what to build nor how people phrase questions as you go into troubleshooting an issue. The other gap is that most of the tools we have right now are not sufficiently collaborative: we need tools that help both the business and the technical sides in building assistive experiences, and then IT can deliver all kinds of back-end infrastructure needed to create the experience.
What kind of changes do you anticipate and what can organizations do to stay abreast of these changes?
There are a lot of solutions out there for customer self service today. When building solutions in that area, companies can anticipate some customer needs through guesswork and then create personalized experiences, which can help make the self-service process more efficient. Unfortunately, this approach is quite short-sighted because customer needs will shift and change over time, and it’s tedious and resource-intensive to reboot that process over and over again. For that reason, we think more companies will turn to AI to help them adapt to and address new customer behaviors on the fly.
We think one of the best applications of AI is to use the best natural language processing solutions you can find to discover all the different ways that customers describe their problems, many of which aren’t obvious. For example, at Chatbase, we often find that some customers don’t even understand exactly what their problem is, or at least how to articulate it. There’s no way to anticipate all the edge cases without taking a data-driven approach to discovering them in past customer interactions. So, based on insights you’ve found in that data, you can more easily anticipate what your main customer issues will be and help them get to resolution faster with an AI-powered virtual agent, whether chat or voice-based. For complex problems, customers can be handed off to live support agents.
How do you see the evolution a few years from now with regard to disruptions and transformations within this space?
Simply put, the technology (including natural language understanding/speech recognition and speech synthesis) are going to get better and better, so most companies should start making investments now and then iterate over time as the tech improves. They should also be precise and smart about how they build the bots, and have flexible designs so that the use case can be changed at any time.
What is your advice for budding technologists in this space?
Whenever new platforms emerge, they bring along loads of opportunities for platform implementers to benefit from them. So, as these platforms for AI-powered customer experiences become accessible and popular among customers, budding technologists should think about building experiences on those platforms to help them bootstrap their business. This is especially true for the startup people out there.
Ofer is the GM of Chatbase, a cloud service for designing, analyzing, and optimizing conversational experiences. (Chatbase is part of Area 120, an incubator operated by Google.) Its newest product, Chatbase Enterprise Edition (available via Early Access Program), helps contact centers unlock hidden insights from customer interactions to get critical data for creating the right AI-powered virtual agent. Previously he served as CEO of Pulse.io, an app performance monitoring service acquired Google, and CEO of Sendori, an ad network acquired by IAC. He is a startup mentor at Stanford and an angel investor in Lyft, Palantir, and Klout. Ofer holds an MS in Artificial Intelligence from University of Michigan and an MBA from Cornell University.
