Does Your Company Really Need a Chatbot?

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Chatbots — automated conversation systems — have become increasingly sophisticated. Chatbots are a broad category that includes everything from Amazon Alexa smart speakers to automated text chat on a company’s customer service page. The most powerful chatbots — and the ones that can actually make an impact on customers’ experience and company bottom lines — are virtual agents. These are chatbots powered by an artificial intelligence that can understand and answer a wide variety of customer questions. Like all successful automation efforts, customers service chatbots can reduce costs, but their true value lies in the improvement they bring to the customer’s experience. Bots are available 24 hours a day, 7 days a week, and often answer customers’ questions more quickly than human agents can. When considering implementation of a virtual agent, business leaders should consider what kind of companies are best served by chatbots, how to integrate them into their existing customer service system, and which distribution channels are most fruitful.

Chatbots — automated conversation systems — have become increasingly sophisticated. Should you design and deploy one that can interact with your customers? If you’re an executive making that decision right now, you may feel caught between A.I. hype on the one hand, and the fear that machines might not treat your customers right on the other.

Chatbots are a broad category that includes everything from Amazon Alexa smart speakers to automated text chat on a company’s customer service page. The most powerful chatbots — and the ones that can actually make an impact on customers’ experience and company bottom lines — are virtual agents. These are chatbots powered by an artificial intelligence that can understand and answer a wide variety of customer questions.

Virtual agents must scan the customer’s request, combine that with whatever other information is available to them (such as their past purchases, account settings, or geographic location), and then identify the customer’s intent: what she’s trying to accomplish. The intents of a telecom company customer might include, for example, “fix my nonworking service,” “reset my password,” “help me move,” or “upgrade my service.” Once it has identified the intent, the virtual agent responds with a script intended to solve the customer’s problem.

Like all successful automation efforts, customers service chatbots can reduce costs, but the improvements they make in customer experience are far more impactful. Bots are available 24 hours a day, 7 days a week, and often answer customers’ questions more quickly than human agents can. At the car rental company Avis Budget, for example, virtual agents were able to identify and automate 68% of service calls. Just as Web automation in the 90s and mobile apps in the 2010s improved customer convenience, properly designed virtual agents can improve customer satisfaction. For example, at the U.S. satellite television operator Dish Network, customers already rate their satisfaction after chats with a virtual agent on par with responses from human agents, and those scores are improving as the virtual agent handles more questions more effectively.

Based on my (P.V.’s) experience developing virtual customer service agents with executives worldwide and our research on dozens of agent deployments— both those from my company and from competitors — we’ve identified the factors that lead to successful implementations (full disclosure: two of the companies discussed in this article, Avis Budget and Dish Network, are clients of P.V.’s firm). When considering implementation of a virtual agent, business leaders should consider what kind of companies are best served by chatbots, how to integrate them into their existing customer service system, and which distribution channels are most fruitful.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.