Beyond Chatbots: How Conversational AI Is Making Customer Service Smarter


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For the past few years, we’ve all been “Let’s chat!” buttons on websites that promise fast, helpful customer service. But heavily hyped AI-powered chatbots, a staple of the customer experience mix since 2016, have also proven to be a mixed bag. Consumers found many bot interactions disappointing and time-consuming. Meanwhile, companies often had to provide much more expensive care and nutrition from chatbots than expected.

Thanks to open-source AI language models such as Google’s BERT and Microsoft/Open AI’s GBT, it is now much easier for organizations and technology software vendors to build on top of these innovations. They can create more advanced AI tools for conversation, from smarter chatbots and asynchronous messaging to voice and mobile assistants. Today, deep learning models can be designed quickly. And, depending on how they’re done, they may only require a small amount of training data, Hayley Sutherland, senior research analyst for conversational AI at IDC, told VentureBeat.

“Over the past two or three years, the ability of machines to understand both written and spoken human language has really, really improved,” she said. “The technology has gone well beyond what we would consider a rules-based, scripted approach where a human manually writes a rigid script that, if it goes beyond that, can break easily and add to frustration.”

Now machines can better understand not only the words being said but the meaning behind them, while also being able to respond more flexibly. “That means we can create much more sophisticated virtual assistants or customer service agents, whether they’re text or speech-based,” Sutherland said.

Solving conversation challenges with customers

Derek Roberti is VP of Technology, North America at Cognigy, a low-code conversational AI platform in Germany. It was named a leader in Gartner’s Magic Quadrant for enterprise conversational AI platforms, along with companies such as Kore.ai, OneReach.ai, and Amelia. According to Gartner, the enterprise conversational AI platform market “addresses the needs of larger enterprises by targeting multiple use cases, conversation modalities (such as voice, chat, SMS, and email), and the ability to operationalize across the enterprise. ”

In general, the conversational AI market in customer service is divided into three main categories, Roberti explained. The first are conversational AI specialists, with platforms with user interfaces tailored to both the technical and non-technical user; turnkey integrations; and a wide variety of channels. “Those are the ones Gartner has named leaders in space,” he said.

Then there are the giant cloud providers, such as Microsoft, Google, Amazon and IBM. “These provide core services, maybe translations, natural language understanding or speech-to-text, but don’t necessarily have that set of user interfaces and pre-built components,” he added. Finally, there are also thousands of other smaller market players taking advantage of open source innovations to provide turnkey tools with varying levels of sophistication.

All of these companies, across all categories, are “working to solve the same problem,” Roberti said. That is, creating first-class customer experiences, especially with tooling accessible to both the non-technical and technical builder. “How can we empower people to build automated interactions that are inviting, easy to get started, and build even the most sophisticated conversations with?” he explained.

Conversational AI targets two types of customer service customers

Roberti lists two primary types of buyers in the customer service and support conversational AI tools market. First, there are buyers who own the contact center or customer-facing support systems. “These are generally non-technical buyers,” he said.

These buyers may have never worked with conversational AI, or have no developer resources, Sutherland added. “That’s why we’re increasingly seeing these types of tools with little or no code,” she says. “You can have someone who isn’t a developer but is an expert at customer conversations – who knows what a good conversation looks like, who can help train and monitor the capabilities of that conversational AI being built and really make sure that the human element is there.”

On the other hand, more tech buyers, including enterprise architects, are getting requests from every part of the organization for chatbot and voice automation features, explains Roberti. “They are looking for a platform that can be used by the entire enterprise. They care about the user interfaces, but they also care about how the tools will integrate into other systems and how it works across security and compliance ecosystems.”

Context-aware conversational AI is essential

Quiq is a Bozeman, Montana-based, AI-powered conversation platform that enables brands to reach customers through the most popular asynchronous SMS channels. According to founder and CEO Mike Myer, first-generation chatbots lacked good natural language capabilities and often failed to give customers access to the right data.

They also had very little context awareness to encourage personalization, Myer explains: “For example, if you recently made a purchase and come back to the website a few days later, it’s helpful if the chat box actually says ‘Welcome back’. question about the order you placed yesterday?’”

Now, however, conversational AI technologies, such as the underlying AI-driven natural language capabilities, are reaching a plateau. “The difference between suppliers when it comes to understanding natural language is imperceptible from the customer’s perspective,” he explains. “What’s different now is the quality of the implementation, the design, how much training went into it.” The UX, he said, “has become the big differentiator.”

Acquisitions lead to a holistic conversation offer

It’s a sign of the huge, fragmented conversational AI market in customer service, as well as the VC money flowing into it, which Sutherland told VentureBeat she’d never heard of Quiq. That’s even though the company recently announced a $25 million Series C funding round and last year acquired Snaps, another conversational AI tool.

“That’s very typical of this space right now, the really big infusions of VC money,” Sutherland said. “We’re really at a turning point where we’re starting to consolidate.”

In fact, acquisitions have become a fixture in the space. Beerud Sheth, co-founder and CEO of messaging leader Gupshup, recently announced three conversational AI acquisitions, including Active.ai and AskSkid, with two more in the pipeline.

“We’re constantly evaluating technology, so if we find another company that has done something interesting that complements what we do, we’ll be happy to consider it,” Sheth said, explaining that the acquisitions will become part of a holistic platform as conversational AI becomes part of what every business needs.

Sutherland also says a smaller AI company, Uniphore, is making interesting acquisitions to complement its AI-powered offering. “One was a company that used AI to analyze video and help salespeople understand customer sentiment,” she explained. “Back then, Uniphore was mainly focused on customer service, but now there’s this sales-focused conversational AI. The idea is that companies can monitor the rest of the customer funnel.”

Tight labor market leads to smarter conversational AI

A tight labor market is driving conversational AI growth in customer service, Roberti said. For example, in the early days of the pandemic, many contact center workers were laid off. “Even if they could hire as many people as they need for 25% more compensation, there is no staff available,” he said. “So companies are being pushed towards automation as a necessity, as a matter of survival.”

The good news is that the latest conversational AI for customer service has the potential to improve the image of an industry previously filled with useless chatbots, Roberti said: “I would say that if you did a customer satisfaction survey in January about chatbots and voice bots from this year and compare it to January 2023, you will see a much more positive response.”

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This post Beyond Chatbots: How Conversational AI Is Making Customer Service Smarter

was original published at “https://venturebeat.com/2022/04/21/beyond-chatbots-how-conversational-ai-makes-customer-service-smarter/”

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