How to leverage customer service AI tools in your business

If you need to talk to customer service, it typically means you have a problem. The last thing you want to do is hold for 30 minutes listening to the same grainy audio on loop. But that’s exactly what we’ve come to expect of the customer service experience.

AI technology is changing that, not just on the front lines, but throughout the entire customer service process. While you can’t replace your support team with chatbots, you can use AI programs to increase your team’s efficiency and improve customer satisfaction.

• The spectrum of customer service AI tools
• Use AI powered chatbots to answer customer inquiries
• Perform automated sentiment analysis
• Manage high volumes of support tickets with text classification
• Enable Interactive Voice Response (IVR) customer service options
• Provide proactive, personalized customer experiences
• Assist customer service teams with automated processes
• Enable more realistic customer service training
• AI for customer service still needs a human touch

From AI powered chatbots and text classification to predictive analytics and generative AI, there’s a wide variety of AI technologies that can improve customer engagement. These tools enable omnichannel customer support and empower service reps to create personalized customer experiences faster.

According to Gartner research, 82% of customers who receive value during a customer service interaction are more likely to repurchase or renew, even when given the chance to switch to a competitor. In other words, effective customer service builds your organization’s brand and bottom line—and AI programs can provide an extra boost.

Chatbots are one of the most common uses of AI technology in customer service. By using Natural Language Processing (NLP) and Natural Language Understanding (NLU), they interpret human language and then form an appropriate response. 

As a result, chatbots can use existing data to respond to basic and frequently asked customer questions like “What’s your pricing?” or “What resources do you have for learning cloud?” Chatbots let customers self-service and find the answers they need without speaking with a rep. But if the chatbot doesn’t understand a customer’s question or have access to the necessary information, they pass the customer along to a human representative. 

Chatbots improve the customer service experience by:

• Reducing wait times and providing instant responses

• Filtering customer queries so support teams only handle complex or pressing inquiries

• Offering scalable 24/7 support

According to Forbes, one company solved over half of their recurring questions with a chatbot, improving their customer experience and reducing costs at the same time.

Already building or using a chatbot? Make sure yours follows privacy and security protocols. Creating a generative AI policy can help. Learn more about AI-based chatbots and how to build a secure one with our course Artificial Intelligence Essentials: AI-based Chatbots.

Feedback is key to customer support. When you understand how your customers feel, what they’re satisfied with, and where they’re frustrated, you can enhance the customer service process.

Rather than manually examining customer feedback, support tickets, and surveys, you can automate sentiment analysis with AI technology. For example, you might task AI tech with flagging feedback as positive, neutral, or negative. Or you might want to identify emotions in customer reviews (happy, sad, excited, or frustrated, for example).

Automated sentiment analysis with AI allows you to:

• Resolve customer complaints faster

• Mitigate bias by using consistent criteria to evaluate and tag feedback

• Understand consumer feelings to improve their customer service experience

A simple prompt like this one in ChatGPT can help you perform a quick sentiment analysis:

Want more prompt engineering tips? Our course Getting Started on Prompt Engineering with Generative AI gives you a closer look at prompt engineering in ChatGPT and how you can use it in your role.

The average company receives 578 customer support tickets per day. And the average customer service response time? 12 hours and 10 minutes.

When your support team faces an ever-growing number of tickets, you can leverage AI and text classification to manage requests. AI and ML-powered text classification automatically categorizes text based on past associations. 

You might use text classification to indicate the urgency of a support ticket as high, medium, or low. You could also use it to identify the topic of the support ticket. For instance, has the customer submitted a ticket for a technical issue, billing question, or some other question? AI programs can help you:

• Prioritize requests 

• Identify and respond to critical issues faster

• Ensure customer service representatives receive tickets that match their expertise

When you call a company and an automated voice asks you to say “one” to hear store hours, “two” to speak with a representative, or “three” to hear more options, you’re engaging with Interactive Voice Response (IVR). 

This technology isn’t new, but AI is enhancing it, allowing customers to have more natural and complex conversations. For example, instead of saying “one,” callers can say, “I want to hear your store hours,” and IVR tech will understand and provide the right information.

In the same way users want personalized social media feeds tailored to their interests, people want personalized customer service interactions that match their experiences and preferences.

Even before someone becomes a customer, AI tools can help curate custom experiences that drive brand engagement and loyalty. For example, a user may have visited your website several times but not purchased anything yet. Using their behavior or the items in their shopping cart, AI tools (like chatbots) can reach out to customers to offer assistance or send them nudges with discount codes that apply to the items in their cart.

From updating records and escalating issues to troubleshooting and collaborating with product teams, customer service reps handle a variety of responsibilities. AI technology like Agent Assist helps support teams manage this workload more efficiently, improving customer satisfaction at the same time. 

By interpreting customer requests, these tools can pull up relevant knowledge base articles to help agents find solutions faster. They can also transcribe calls and prompt the agent with recommended phrases or next steps that have historically improved the customer experience. 

Even without dedicated AI tools like Agent Assist, customer-facing employees can use generative AI to create emails, craft custom responses, and streamline their workflows. Make sure they have AI training to understand this technology and how they can use it in their daily responsibilities.

When faced with frustrated customers or a question they don’t know the answer to, customer service agents are expected to remain calm. That’s a difficult skill to cultivate without training.

AI tech can be a training tool that assumes the role of a customer. Your reps can practice interacting with a “customer,” honing their responses, and getting familiar with common scenarios.

AI technology isn’t a replacement for your customer service team. It’s a tool they can use to work more efficiently. After all, there are still challenges associated with using AI programs for customer service:

• Hallucinations and biased data

• Lack of empathy

• Security and privacy risks

If you’re ready to start using AI in your customer service process, we offer beginner, intermediate, and advanced AI and ML courses to empower you and your teams to make the most of this emerging technology.

Don’t know where to begin? Here are some AI courses to help you get started:

• ChatGPT and Generative AI: The Big Picture

• Getting Started on Prompt Engineering with Generative AI

• Navigating Generative AI Hurdles: Prototyping, Evaluation, and Ethics