December 14, 2019

AI for Customer Support Workflows: Opportunity Awaits

AI for Customer Support Workflows: Opportunity Awaits

 Artificial Intelligence is a major breakthrough for customer support functions, offering answers in real-time and asking intelligent follow-up questions. Customer support and service areas are ideal candidates for AI-enabled improvements because modern, readily-deployable AI tools are able to work in tandem with human agents. The right AI applications can streamline processes and expedite information gathering, letting customer support staff do what they were hired to do: actually support customers.

This should be good news for most companies since Gartner estimates that within a few years, 89 percent of businesses will mostly compete on customer experience. But AI can’t develop in a vacuum. It needs to gain knowledge of how a business successfully confronts its most-common issues.

Many companies already have customer support data readily available whether in the form of training data, existing customer support interactions, and/or common support issues. Just like with humans – the best way for a machine to become adept at customer support is through immersion.

Read More: The Future of Work’s Most Crucial Component: Artificial Intelligence

Training Data and FAQs

Imagine you are learning to perform a job. A detailed description of that job is integral. Just like a human, AI needs support documentation to get up to speed. If Artificial Intelligence can observe human support staff turning customer problems into documented solutions, AI can learn how to help do this kind of work, too. For instance, if your business has an FAQ list that’s reliable, that’s a prime candidate for inclusion in an AI system.

Ideally, an organization already has clear and comprehensive support documentation, but if that’s not the case, then you will need an AI support solution that can help you build, validate and maintain documentation.

Customer Support Interactions

Both AI and live customer support workers are charged with translating customer questions and complaints into structured queries that prompt documented solutions.

In practice, having a mix of both is optimum. AI can document your human staff interacting with customers and coaxing additional information out via follow-up questions. Whether human or AI, the role of such workers is the same: Collate data into a set of likely problems and then research those problems for likely solutions—especially critical if there are knowledge gaps.

The caveat here is that this type of communication needs to be written down. Email, chat and other text-based communications are ideal for AI. Voice-based communication can also work if you’re willing to invest in quality transcriptions.

Read More: Employee-First Approach to Digital Transformation Showing Greater Returns

Common Support Issues

As with many new innovations, AI initially appeals to some parts of the business. Customer service is the most likely area to gravitate to the use of AI first. Using AI can dramatically reduce the average time it takes for a customer service worker to handle inquiries.

As long as a good portion of your customers’ support issues have known answers,  AI will free up human workers to handle more complex problems.

 Working with AI

 Despite what you may see or hear in the media, AI systems aren’t magic they are computing systems that need a base of written instructions. AI also needs to observe how human staffers handle queries in order to learn how to do the same. As AI continues to learn, its benefits will grow non-linearly with time.

Infusing AI into your customer support workflow will dramatically reduce the average time a support rep takes to handle inbound support requests. Over time, AI will evolve to make your organization more reactive and thoughtful. More intelligent, in other words.

Read More: 5 Ways a Modern Mobility Program Can Help You Win the War for Talent

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Rob May

Rob May is the CEO and Co-Founder of Talla, providing AI Powered Prediction, Automation, and Augmentation to Service and Support Teams. Previously, Rob was the CEO and Co-Founder f Backupify, (acquired by Datto in 2014). Before that, he held engineering, business development, and management positions at various startups. Rob has a B.S. in Electrical Engineering and a MBA from the University of Kentucky.

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