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Technology Automates Agent Interactions

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Paul Korzeniowski's picture
B2B Content producer Self-employed

Paul is a seasoned (basically old) freelance B2B content producer. Through the years, he has written more than 10,000 items (blogs, news stories, white papers, case studies, press releases and...

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  • Apr 23, 2020

Traditionally, customer services centers have required significant manual resources, tens, hundreds, and even thousands of agents. The emergence of artificial intelligence based technologies is altering that equation, so much so that utilities now need to plan for contact centers where the bulk of their interactions occur via machines rather than people.  

Recent advances in communications; artificial intelligence and machine learning; voice recognition; chatbot;, and natural language processing provide utilities with new customer service options. Out go the legacy business processes; in comes a new wave of intelligent, automated solutions.

Why make the change? $$$. Surveys find that utilities spend about $5 to $10 whenever an agent handles an inquiry. Automating the process lowers that expense to a few dollars.

But lower costs are not the only benefit businesses can reap. Satisfaction improves. Customers have become much more comfortable with automated self-service and increasingly expect it. Utilities can thank consumer focused intelligent virtual assistants, such as Amazon’s Alexa and Apple’s Siri, for driving that change.

What Works?

So, what tasks are these new computer based systems suited to? They can handle many routine interactions, such as order modifications; order cancellations; turning energy services on and off; and routine billing inquiries, like checking a person’s balance. They also are suited for targeted outbound communications: Instead of waiting for customers to pick the phone, utilities send to customers in areas without power information about the problem via automated voice systems, texting, email, or a combination of all of those options.

But utilities need to put thought into the design of these applications. In simple cases, customers find the approach helpful because it quickly provides them with needed information, usually to straightforward question. For complex issues, automating the process becomes more challenging because there are so many variables. As a result, the automated, self-service options need a logical design and flow. But people think differently, so the layout needs to include a variety of entry points, all leading to the same end point: resolution of the issue. A poor design may result in more calls to agents and lower customer satisfaction.

Contact centers play a central role in empowering utilities to service consumers but they often extract a high price. Recent technical advances offer utilities the ability to offload routine interactions. This step has the potential to lower utilities’ service costs significantly but thought needs to be put into system design for the change to be effective.


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Andy Gotlieb's picture
Andy Gotlieb on Apr 30, 2020

Paul, this all sounds good in concept, but in reality I'm guessing there are still going to be problems. As you noted, these kinds of systems may be best for routine transactions, but personal experience shows that oftentimes customers simply start shouting "operator" when they get sent down a rabbit hole of unsatisfactory options.

In addition, there still seem to be plenty of bugs with voice recognition. If I ask my Alexa 10 questions, I can count on "her" improperly answering at least three or four of them.

Of course, technology will continue to improve and the cost benefits, as you outline, are certainly worth pursuing, but it would behoove any utility (or any business for that matter) to proceed slowly along this path.

Paul Korzeniowski's picture
Paul Korzeniowski on May 1, 2020


Yes, the technology is not perfect -- and it never will be. These solutions become better as vendors gain more experience and more data, so they can tweak their algorithms. They are markedly better now than six or twelve months ago. The issue seems to be determining how to use them effectively. As noted, they work for certain simple functions but fail as more complexity is introduced. The key is not overreaching when building the application.


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