AI in Customer Service: How It’s Used, With Examples

Many organizations are using artificial intelligence (AI) to improve their customer service operations.

One common approach is using a chatbot or virtual agent to have conversations with customers that resemble the dialogue they’d have with live agents. This use of AI allows companies to provide more engaging customer service around the clock while freeing up team members to work on other tasks.

Although this technology is new and still developing, AI offers the potential to change the way organizations interact with their customers as they provide ongoing service and support. This article digs deeper into how AI intersects with customer support and what forms of conversational AI are currently available.

Understanding AI in customer service

When we talk about AI in customer service, we’re talking about the integration of AI technologies, including machine learning, natural language processing (NLP), and automation, to improve customer interactions.

Machine learning equips systems to perform tasks even if they weren’t programmed for that specific purpose. AI systems are trained on a company’s data before being put into service, and are also capable of continuing to learn and improve their ability to provide more accurate answers over time. AI can learn from previous conversations about which responses are most helpful.

Customer service uses two types of artificial intelligence. Rule-based bots respond to customer questions based on a predetermined order of instructions. In other words, you may select one choice from three or four provided options and receive additional preset choices based on the prompt you select.

Conversational AI works differently. Through NLP and machine learning, conversational AI can quickly process customer text prompts and respond in a conversational manner. Rather than forcing customers to choose from a preloaded set of options, conversational AI chatbots allow them to enter their own questions or prompts.

The AI takes that input, compares it against its training data, and provides an output that its algorithms predict is most likely desired. Its output is grammatical and conversational, and the customer can respond to it with more questions.

Benefits

Using conversational AI tools in customer service offers a range of benefits that can be valuable for both customers and organizations. AI can offer faster response times, 24/7 availability, and tailored solutions.

In the past, companies could only respond to customers if they had support teams on the clock. Thanks to AI, businesses can provide nuanced and detailed responses even without support agents working in the contact center. In industries with complex needs, the AI can be used to answer basic questions, and can filter customers with more challenging needs to an operator. This can be very beneficial to both businesses and their patrons.

AI also allows businesses to analyze large amounts of customer data, gain insights into customer preferences and behaviors, and deliver personalized recommendations and support. This means they can meet and exceed customer expectations, leading to higher customer satisfaction, improved retention rates, and business growth.

Challenges

Using AI in customer service can provide many benefits, but it also poses several challenges.

• Data privacy and security concerns. Implementing AI in customer service operations requires organizations to address data privacy and security concerns. Storing and protecting customer data is crucial, and businesses should be transparent about data usage and access to build trust with customers and stakeholders.
• Maintaining a balance between automation and the human touch. While conversational AI chatbots can simulate human-like interactions, they can’t fully replace the experience of talking to a real human agent. Businesses should strike a balance between automation and human involvement, especially for higher-priority requests or complex concerns that may require human intervention.
• Integration and system complexity. Some AI systems may not seamlessly integrate with existing business systems, requiring partial or complete system overhauls. This could be due to varying compatibility and complexity factors associated with implementing AI technologies.
• Training and monitoring AI systems. AI is only as good as the data used to train it. AI trained on too little data will be unable to make accurate predictions when given a new question—this is called over-fitting. And AI trained on false data, or data that contains biases, will be prone to giving inaccurate or biased feedback. As the AI is put into use and continues to learn, the value of its responses must be carefully monitored.
• Customer acceptance and adoption. Some customers may hesitate to adopt AI-driven customer service, particularly if they’re accustomed to interacting with real human agents. Factors like trust, familiarity, and perceived value of the AI service can influence customer acceptance and adoption.

The common theme among potential challenges is the need for education from the beginning. Businesses should ensure team members, stakeholders, and customers understand how the company plans to use AI.

How to use AI in customer service

Now that you have a basic understanding of how AI functions, you might wonder what it can do for your business. We cover a few common applications of AI in customer service.

Chatbots for handling customer queries

AI chatbots are virtual assistants that use NLP and machine learning to interact with customers in real time. They can offer personalized recommendations, address frequently asked questions (FAQ), initiate transactions, and provide support across multiple communication channels like websites, messaging apps, and social media.

ChatGPT is a popular example of an AI chatbot. With ChatGPT, you can enter a short text prompt and receive a conversational response. Other examples of chatbots include Jasper, Bing, and YouChat.

Let’s say a customer hasn’t received a product they ordered a week ago. A chatbot can respond to the customer’s question about their order status while apologizing for the delay and asking follow-up questions, such as, “Would you like the tracking information for your package?”

In this example, the customer finds the help they need and receives support without waiting for a live agent. In the meantime, businesses can serve customers even if they don’t have a human agent available to handle the request. This can streamline the customer service process.

Sentiment analysis for customer insights

AI can analyze customer interactions, including chat logs, email, social media posts, and surveys, to gauge customer sentiment and satisfaction. Sentiment analysis algorithms can identify positive, negative, or neutral sentiments. This data helps businesses understand customer preferences, pain points, and trends, enhancing the overall customer experience.

Conversational AI systems improve over time as they use data from previous conversations to improve the answers provided for future prompts. Conversational AI platforms also use sentiment analysis to decipher the emotional tone of the response, further helping the system improve its conversational responses.

Finally, AI can use sentiment analysis in conversations to gain a better understanding of trends and patterns that may develop from speaking with several customers. Businesses can use this data to better understand their customers.

Integration with CRM and service tools

AI integrates with customer relationship management (CRM) systems and service tools to provide a comprehensive view of customer data and interactions. AI can analyze customer information and behavior while providing valuable insights to customer service agents. Agents can then deliver personalized and proactive support, access relevant customer data during interactions, and track customer history.

AI makes it possible for companies to create more personalized marketing content tailored to specific needs and customers. Assuming customers opt into this type of marketing and their data is handled ethically and properly, this form of marketing can lead to enhanced customer engagement, improved targeting, and increased conversion rates.

Self-service and knowledge based systems

AI self-service systems allow customers to find answers to their questions or resolve issues independently. These systems can interpret and respond to customer queries, search knowledge bases, and provide relevant information or step-by-step guidance. Customers can access FAQs, tutorials, troubleshooting guides, and interactive tools.

This improves the customer experience by streamlining the search for relevant information and materials. Rather than searching through a company’s website (or through a search engine) for a how-to guide or instruction manual, customers can receive instant help from a conversational AI chatbot that leads them to the exact resource they need.

Companies using AI in this way can expand their offerings while freeing up team members who previously responded to customer questions and concerns. Since AI automates many of the repetitive tasks they work on, human agents can begin to work on new projects and goals.

Routing and escalation of customer requests

AI can automate the routing and escalation of customer requests to the most appropriate support channels or agents. AI systems can analyze customer queries and context to direct inquiries to the right department or individual, resulting in faster resolutions and minimal customer effort.

Companies can use this type of routing to promote better customer engagement. They can handle a large percentage of customer concerns through the AI system while still offering personalized engagement when necessary.

3 Examples of AI in customer service

Companies across various industries have widely adopted AI to enhance the customer service experience. We cover three real-world examples of companies using AI to improve their customer service.

Chipotle

In September 2022, Chipotle announced it would pilot an advanced AI technology to help with kitchen management at some Southern California restaurants. The purpose of this cutting-edge system was to provide real-time updates about demand so cooks could prepare the right amount of food and reduce waste. The system monitors ingredient levels and tells cooks when to begin preparing food.

Early returns on the system were positive. Studies show the pilot project improves kitchen operations while providing guests with fresher meals.

Netflix

Netflix is actively looking for ways to improve its algorithms through AI. In addition to improving the streaming platform’s recommendations for which TV shows and movies viewers may find interesting, Netflix is using machine learning to optimize its original content production.

Netflix is also finding ways to use AI to develop better advertising campaigns. With over 232 million paid subscribers, Netflix has a large testing ground to try its innovative ideas and fresh approaches.

1-800-Flowers

One benefit of ordering from 1-800-Flowers is that customers can use the company’s NLP-powered virtual gifting assistant if things don’t go according to plan or they need information about their order status.

In addition to offering a voice-based service that helps customers deal with issues and track their orders around the clock, the system can also offer “just for you” recommendations for customers who create an account in the 1-800-Flowers mobile app. The AI agent learns from each interaction and studies the customer’s order history to ensure service becomes more personalized as time goes on.

Boost your customer service with AI and Upwork

AI-powered customer service should continue to evolve as potential advancements in generative AI and machine learning continue to develop. Going forward, AI will continue to integrate at different points across the customer journey to improve and streamline existing operations. In the meantime, companies will continue to look for ways to improve their existing operations and provide new solutions to old problems through the use of AI.

Are you interested in finding a talented professional to help you reap the maximum benefit from AI in your business? Check out Upwork to find a talented AI engineer who can help with your next project.

If you want to work in AI, you can find plenty of AI jobs on Upwork, as well. With average salaries for AI developers ranging between $25 and $50 per hour, it can be a lucrative field to pursue.

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