The Five Most Key Takeaways from This Blog
- The recent boom in conversational computing platforms related to developments in generative A.I. has brought customer service solutions to a new level.
- The traditional tool for AI in customer service is the chatbot. These can be implemented on websites, social media accounts, and other areas of cyberspace.
- Progress in information retrieval, data analysis, and machine learning in general has made it much easier to train chatbots that can effectively answer questions. That, and continually learn answers to questions. That plus also assisting human customer service reps searching for answers.
- Major tech companies are getting in on the customer-service A.I. trend, with Microsoft’s recent CoPilot customer service announcement evincing this.
- Business owners will need to determine a “Goldilocks” amount of AI in customer service operations. Too much A.I., and customers will feel as if they need to scale a wall of computer algorithms to get a human solution. Too little A.I., and the human employees may be stuck with a comparable level of toil and overwork as before.
I Understand Your Frustration. Now Would You Please Hold?
The advantage-disadvantage for businesses is that customers rarely expect a great service experience, setting a low bar to meet.
Instead, they brace for the possibility of an unpleasant argument over a grievance, once the Muzak stops and the ringing begins. Or, alternatively, a problem that may or may not be soluble.
A few bad experiences can taint a customer’s perception of all future customer service interactions.
The advantage: the bar is low, so it’s easier to achieve a perception of a halfway decent customer service experience.
The disadvantage: your customer service team must handle customers who might already expect the worst from the conversation.
And that is just the beginning of the challenges.
Tackling Customer Service Challenges with A.I.
Smaller, routine questions clog phone lines, diverting attention from more pressing issues that truly need a phone conversation.
Implementing Conversational Computing
Long wait times and smooth jazz suggest a constant high volume of customer service calls for large companies.
And how many of those calls could so easily be answered by a chatbot in a quick ask-question-get-answer interaction online?
Probably a percentage that overwhelmed customer-service reps would describe as impreferably high.
Hence, the existence of the chatbot.
For customers who would check out the website before bothering dialing the customer-service number, the chatbot can be a good way to satisfy any of the easier (though still significant, of course) queries that a customer may have about your business, products, and/or services.
These chatbots can actually become much more knowledgeable through machine learning, allowing them to learn on the fly to gradually improve their conversational ability, and any changes to policy that you may have.
But when the human customer-service rep is indeed on the line, the A.I. assistance need not stop there.
Instead, the A.I. can be available to that rep in the form of a conversational computing application that allows for quick information retrieval. Instead of having to scour the customer-service manuals for the protocol in handling a specific problem, the rep can delegate that task to the A.I. From there, the chatbot can quickly retrieve the info that is necessary to resolve the issue.
The Goldilocks Customer Service Zone
Ultimately, the big challenge for companies is to find the just-right amount of customer service A.I.
The goal here is to preserve human interaction in the areas that matter, and to make the humans actually reachable. (One of the banes of many customers’ existences are the automated phone systems that make people jump through too many robotic hoops to actually get a human on the line.)
Business owners will need to experiment to find what is right for their own operations. Working directly with customer-service teams to figure out the optimal A.I. implementation can be one promising avenue in getting started.
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