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Grow Your Business Technology

Conversations with AI: Navigating the World of Consumers and Chatbots

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It can take weeks to get used to the quirks of working on a Mac. / Credit: Shutterstock

One of the most visible ways artificial intelligence (AI) is entering the business world is the consumer-facing chatbot. This AI-powered virtual assistant uses natural language processing to understand key words and context from customers and help them without the use of a human representative. Naturally, this offers powerful incentives to companies looking to offer 24/7 customer service without ballooning costs.

But how are consumers reacting to chatbots? Are they really an effective way to augment customer service or are they a finicky, early stage technology that still has too many bugs to work out?

Business News Daily spoke to consumers and companies that have stepped into the world of AI in customer service to find out more about how chatbots are evolving and changing the way we think about customer service and sales automation. [Check out these big trends that illuminate the future of customer service]

There are two primary types of chatbots: one works on a rules engine, and the other is powered by machine learning, a subset of AI. The rules-based bots are a lot simpler and won't understand complex commands and requests, or be able to discern context.

The machine-learning versions, however, are more adaptable and intelligent. They can better understand context and react appropriately, especially as they interact with more humans over time. Machine learning incorporates natural language processing to do this, and as a result, can carry on far more sophisticated conversations than their rules-based counterparts.

Chatbots engage consumers on messenger platforms – which are quickly becoming the No. 1 place users spend their time, especially on mobile – and you'll need to determine where yours will exist prior to development. Facebook Messenger and Slack are common places to build chatbots, or you can host them locally on your own website.

As soon as it's live, your customers can begin interacting with your chatbot, which can answer questions, facilitate purchases and more. The more your bot interacts with people, the smarter it gets. That's the beauty of machine learning.

Do chatbots really work in the real world as well as they do on paper? AI has been around for a while, but its development has been a story of peaks and valleys. Can machine learning-based chatbots really be so reliable? The short answer is sometimes.

"In a time where automation is prevalent, personalization is key to connecting with customers, and chatbots have helped personalize that experience," Albizu Garcia, CEO of GAIN, told Business News Daily. "However, there are drawbacks. Chatbots cannot always translate needs and may respond inappropriately to a customer's request. There is no doubt that chatbots are here to stay, but there are limitations that will need to be resolved, like increasing response capability, should they be the future of customer service."

Still, chatbots are a new phenomenon, and continuous improvements and new iterations are being developed every day. Jill Bourque, CEO of RushTix, said her company's chatbot – nicknamed Roscoe – is powered by IBM's Watson Conversation technology and has already positively impacted business even as they continue to work on it.

"Through our chatbot, we've been able to streamline our customer service experience so that users can discover and RSVP to events in a simple, fun and easy way," Bourque said. "We're also continuously improving the chatbot to share more relevant recommendations. The ultimate vision is … a chatbot that knows exactly what users like and proactively sends them events tailored specifically to their interests."

Customers like a human experience, even when they're dealing with a machine. In fact, customers tend to prefer chatbots that are so convincingly human that they might well be speaking with a customer service representative. That is why natural language processing is so important.

"Some website visitors also commented that our chatbot seemed too "robotic" and lacked a personal touch," said Peter Yang, co-founder of ResumeGo. "However, many large companies have been placing a lot of emphasis on research in artificial intelligence and its application to chatbots in very recent times, so the future for this technology looks extremely promising."

A close cousin of the chatbot has emerged in the world of finance as well. Known as robo-advisors, these algorithm-driven bots offer financial planning services to clients without human supervision. These advisors gather information directly from clients to determine specifics about their financial situation and goals, and then leverages that data to offer insights and advice.

Robo-advisors offer direct, around-the-clock assistance to clients and provide personalized, on-demand services, which are increasingly desired by customers and add a selling point to any business. From the business's perspective, robo-advisors can save costs and increase accessibility. They're also cheaper, averaging a flat fee of 0.2 to 0.5 percent, while human advisors often charge rates from 1 to 2 percent.

"Robo-advisors are great, especially for single folks with no children looking to retire at 65 because they are so inexpensive and take into account basic risk characteristics like age and income," said Akash Ganapathi, co-founder and CEO of Trill AI. "The downside to relying on robo-advisors comes when you have a more challenging or unique financial situation or goals like debts, children, marriage, hobbies or divorce. A human advisor can … account [for] your personal habits and needs when creating a financial plan. A robo-advisor cannot, yet."

Unlike their more sophisticated machine learning-based chatbot counterparts, robo-advisors still rely on rules engines, complex though they may be. Ganapathi said the flowcharts used by advisors tend to be more general and consider people in more typical circumstances. The messier someone's personal financial situation becomes, the less likely the robo-advisor will be likely to offer adequate advice. That won't be the case for long, though, Ganapathi predicted. As AI improves, so too well more complex functions like financial advice.

"The future will be robo-advisors capable of even better and more personalized decisions leveraging advancements in artificial intelligence for a similarly inexpensive price," he said.

Adam C. Uzialko

Adam received his Bachelor's degree in Political Science and Journalism & Media Studies at Rutgers University. He worked for a local newspaper and freelanced for several publications after graduating college. He can be reached by email, or follow him on Twitter.