By Kelly Richardson, co-founder of Infobrandz. She likes to help people build businesses through visual communication and her influential blogs.
From self-driving cars to fraud prevention, artificial intelligence (AI) has long transcended the “buzzword” label. And two years into Covid-19, AI assumes an expanded role in the customer service landscape.
For one, companies started using AI to automate customer behavior pattern analysis — processing gigabytes of data at a velocity that humans can never match. AI can also massively boost response times, proactively detect sentiment, forecast trends and suggest action plans through natural language understanding (NLU).
Despite AI’s unmistakable capabilities in modernizing customer experience, its potential can be severely fettered by the rocky implementations of panicking businesses.
It has become the knee-jerk reaction of some companies in a scramble to address customer service challenges in the new Covid-19 reality. The good news is all of these AI pitfalls can be easily resolved if not avoided outright.
The trick is to detect and understand the potential blunders — ideally before the symptoms appear.
Here are some of the biggest mistakes that companies make in merging AI with customer service.
Shep Hyken, award-winning customer service and customer experience (CX) expert, reminds us that “Customers are people, not numbers.”
A lot of businesses that carelessly integrate AI into customer service treating consumers as numbers on a spreadsheet.
They bet on the accuracy of customer metrics and scorecards when configuring their AI-powered service workflows. As a result, customers are left with hollow experiences that are miles away from helpful or genuine — let alone satisfactory.
Sure, these businesses craft custom “personas” that reflects what a real-life customer thinks and behaves like. But in reality, only a fraction of most companies’ customer bases will match up to these templates.
In order for AI to make a positive, sustainable impact on customer service, a healthy dose of personal, human touch is needed. Live agents should know when to step in and fine-tune interactions based on the priority and uniqueness of accounts. At the very least, your automated workflows should utilize historical customer data to optimize the language, tone and support aspects of your customer service.
Lagging Behind Customer Expectations
Convincing customers that AI is good for them isn’t the problem. In fact, Salesforce confirms that 60% of customers welcome the use of AI in engagements if it means a better experience for them.
But as the function of AI in customer service grows, so do customer expectations.
With the promise of AI, customers expect a frictionless service with unrealistically quick resolution times. On top of that, they expect a handful of other things:
• Visible proof that action is being taken as per their request
• Self-service options
• Multiple options for customer service
Most importantly, they want the quality of their experiences to be consistent across every device they own, especially during quarantine.
Problems arise when your AI-driven customer service isn’t compatible with the omnichannel. So, before you shift your attention toward automation, make sure your system meets all the expectations above on a basic level.
Ignoring Real-Time Signals
With AI at the helm, customer service workflows sometimes become too rigid — shrugging off customer sentiment and causing businesses to miss opportunities to turn losses into wins. That’s because not all AI customer service applications are attuned to real-time signals that can help companies respond appropriately, rapidly and successfully.
According to a 2022 survey by CompleteCSM, 82% of businesses successfully used AI capable of reading real-time signals to reverse negative interactions and bolster customer satisfaction.
With real-time signals, businesses can provide tailored, priority service to high-value accounts moments after an interaction.
As Amit Ray, author of Compassionate Artificial Intelligencesays, “As more and more artificial intelligence is entering into the world, more and more emotional intelligence must enter into leadership.”
Not Preparing Staff For Bigger Tasks
For a lot of businesses, the purpose of AI in customer service is to automate easy, “boring” tasks. Behind this objective is the intention to ease the load of real agents, enabling them to focus more on complicated tasks that AI can’t handle.
Unfortunately, this comes with a downside.
With repetitive cases being automated, your staff will have no choice but to grapple with a heavier workload filled with difficult tasks. To keep motivation and energy levels high, support your staff with adequate training that will prepare them for bigger challenges.
Of course, there’s also the issue of working with AI to provide stellar service.
AI should be able to point to the best courses of action and product recommendations, while humans should be able to make the right calls. Once your staff is equipped with the know-how to seamlessly work with AI, resolution times will drop, employee burnout will be avoided and everybody wins.
Not Measuring Success (And Failure)
Forgetting to monitor and optimize automated systems over time could be the downfall of your AI-powered customer service.
Remember, AI doesn’t mean eliminating human involvement altogether. As customer behaviors and sentiments change over time, even the most optimized customer service workflows can become obsolete.
Track, adapt and don’t be discouraged if AI doesn’t do the “magic” you expect it’ll do to customer service.
After all, the effectiveness of AI heavily depends on human input. Measure everything, double down on what works and cut off needless automation that does more harm than good. Never automate for automation’s sake.