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Modern Self-Service Solutions Become Smarter with AI

Omni-Channel Customer Engagement Article

Modern Self-Service Solutions Become Smarter with AI

 
June 01, 2016

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  By Tracey E. Schelmetic, TMCnet Contributor

The goal of any company should be to make the customer’s journey as easy and delightful as possible. Depending on what business or industry the company is in, this can be achieved in different ways (customer support for Lear jets, for example, will be very different than customer support for clothing). Customers like to help themselves, so self-service should be the first line of support, followed by live agent help via telephone, chat or social media, for example. In the omni-channel customer support environment, the goal should be to deliver a high level of autonomy for customers to solve simple problems on their own, elevating the role of contact center agents to trusted advisors in solving more complex issues.


Luckily, technology has evolved in a way that makes it easier than ever to help customers help themselves. Technologies such as chat or text coupled with analytics, artificial and natural language processing have merged to form a next generation of self-service in the form of chatbots. Thanks to more advanced “design once, deploy anywhere” self-service platforms, solutions providers such as Aspect (News - Alert) have been able to help their customers deploy highly usable and high quality self-service channels such as chatbots.

When we think of chatbots, it’s hard not to think of the first generation of these supposedly helpful automated chat solutions. Many of them weren’t very usable and responsive, and they acted essentially as a barrier to customers getting support rather than a primary means of support themselves. In a recent blog post, Aspect’s Alyx Kaczuwka noted that the next generation of much more usable chatbots actually have “humans behind the curtain.” They’re also smart, so they can “learn” from previous interactions

“Many concierge services are using supervised learning, hiring a multitude of AI trainers to scrutinize any data where the AI’s confidence in its assessment is low, and adjust it accordingly,” wrote Kaczuwka. “This adjusted data can train the AI model to answer similar questions better in the future; in the short term, however, the customer won’t be aware of whether it was the AI or adjustments by a person that yielded the right answer to any particular question.”

Chatbots, therefore, can act as a frontline for customer interactions, ensuring high quality self-service for those who want it but also transitioning seamlessly to live help for those who need it (or prefer it). As companies continue to use these smart chatbots, they may find they can automate more calls as the solution “learns.”

“For customer service, where a personal touch is often appreciated, our approach is to automate the most common inquiries and support a transparent transfer to a live agent – who can identify as such – when needed,” wrote Kaczuwka. “Depending on the nature of the inquiries fielded by the live agent, the information gathered from these interactions that make it to live status could be used to give additional training to their bot, or can remain within the domain of live agents.”

Omni-channel customer engagement is a journey, not a destination. As new channels and new technologies become available, the most cutting-edge companies will continue to refine their processes and make them smarter. When these channels can make themselves smarter automatically, the transformation of the customer support experience will happen even more swiftly.          



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