How AI in Customer Service Helps Humans Do More Than Ever Before
AI is changing every facet of our lives, from the way we cook to the way we work. Customer service is the most important aspect of any business. It defines the relationship between business and customers. Like all aspects of work, AI is changing how we approach customer service.
Full Automation? More Like Fool Automation
People often conflate artificial intelligence with completely autonomous systems. That’s not always the case. In human interactions, especially tense ones, it’s rarely desirable. Have you ever been excited to access a phone tree system or autoresponder? Do you know anyone who was? The human touch is critical.
How accurate would a system need to be for you to let it deal with an irate customer? For it to dispense medical or financial advice? While AI is suitable here, producing such high fidelity systems is often too costly. You have to be deliberate about ROI. Often, it’s more effective to augment humans with AI. A blend often has better efficiency and quality than full automation or humans alone.
Building Super Humans with AI
Here are some common ways AI can improve customer service work.
Triage
Whether it’s the ER or the local help desk, requests must be sorted and serviced in some sane order. Often the person triaging these incoming issues also has the ability to treat them. Wouldn’t their skills be better used in fixing the problems? Many severity and complexity estimating tasks can be handled by AI, including medical triage. Automated triage can reduce bias, time-to-service, and per-issue overhead.
Demand Forecasting
Machine learning can predict customer behaviors, like high demand, from historic data. This allows you to be efficient with stocking and staffing. Ideal staffing provides ideal customer service while minimizing hours. It may also free up your business intelligence people to perform other tasks.
Sentiment Analysis
A common concern with feedback surveys and customer interactions is “Are they satisfied?”. Sentiment analysis tools exist to answer this question. More advanced natural language processing tools can further sort negative interactions by category. Human workers can then rank each cluster of negative feedback and address them in turn.
Data Management
AI can help collect, filter, and analyze customer data in service management portals. It’s especially good at deconflicting records, that is identifying James and Jim are the same person. This can reduce the load on our business intelligence professionals. It also empowers workers to make data-driven decisions, identify trends, and personalize interactions.
Benefits of Human-AI Collaboration
Efficiency
Human-in-the-loop AI systems streamline workflows. An efficient workflow means higher throughput. That is, more requests serviced per man hour and shorter time to first response. Nothing makes a customer feel more valued than a prompt resolution.
Personalization
Tailored experiences have higher engagement, but can be expensive to produce. AI can provide insight into a customer’s preferences and behaviors. This insight reduces the cost of producing a custom-tailored response to a customer.
Focus on Complex Issues
AI’s biggest benefit is that it often takes care of the busy work that’s necessary to do a job. Data entry isn’t adding value. Neither does report generation; all the value is in having the data. Freed from the mundane, workers can focus on problems requiring empathy and creativity.
Challenges and Considerations
Integration Complexity
Your customer service offering is supported by existing systems and solutions. Chances are you have a whole pile of them. Adding a new system to the menagerie is always tricky, and AI is no different in this regard. It comes with the common technical and human factors challenges. To successfully onboard AI, you must invest in implementation, training, and support.
Data Privacy
To paraphrase The Notorious B.I.G., “mo’ data, mo’ problems.” AI techniques are often data hungry. As such, AI applications need good data privacy and governance frameworks to be in place. Otherwise, you risk harming your customers and running afoul of the law.
Human Adaptation
Employees might resist AI integration due to fears of job displacement. In general, human in the loop systems increase throughput. This can, but needn’t, result in reducing headcount. Most of us are desperate to do more with our fixed time. Clear communication and empathy are essential in any process change, doubly so with AI.
AI is best as an aide for customer service, rather than a replacement. Businesses giving their customer service teams AI tools increase efficiency, personalization, and throughput. This drives improved customer satisfaction and, ultimately, loyalty. Blending AI’s capabilities with human empathy and creativity is the key to success.
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