You’ve probably heard the incessant buzz about how Artificial Intelligence is already causing major changes in the customer service game.
But between all the hype and confusion, you might be wondering - is AI really ready to interact with your clients? After all, they’re the most important part of your business!
Stick with us, and we’ll walk you through 12 solid examples of AI in customer service.
We’ll cover:
Let’s get started!
Chatbots, virtual assistants, and other AI technologies have made incredible strides in recent years.
Many businesses are already harnessing AI to improve customer service in meaningful ways.
The question is, is AI really ready to take center stage? The short answer is yes.
But let’s look at how Artificial Intelligence systems are making that happen:
Chatbots are changing customer service by handling routine inquiries with major precision and efficiency.
For instance, as we pointed out above, AI chatbots can reduce call volume by up to 30% by automating answers to common questions like business hours or order status.
This not only streamlines customer service operations but also allows human agents to dedicate more time to complex issues that require a personal touch.
An example: A customer inquires about return policies through a website chat. An AI chatbot, powered by Zendesk, instantly recognizes the inquiry's intent and provides a detailed response based on the company's return policy, including steps for initiating a return.
Voice assistants help customers interact with services without the need to type or navigate through menus.
By integrating conversational AI, businesses can offer support for tasks such as checking account balances or making reservations, all through simple voice commands.
Further, research indicates that voice assistant solutions can improve customer satisfaction rates by enhancing accessibility and convenience.
An example: A customer asks their voice assistant to check the status of their recent order. The assistant, integrated with a powerful AI, accesses the customer's order information and verbally provides an update on the delivery status.
AI technologies are excellent at managing large volumes of emails by categorizing them, prioritizing urgent messages, and even drafting responses for routine inquiries. This can lead to a reduction in response times by up to 50% – a tremendous win for customer satisfaction.
An example: A customer service inbox receives an email concerning a defective product. An AI triage system like Lindy sorts this email into the high-priority folder and drafts an initial response apologizing for the inconvenience and asking for product details, ready for an agent's review.
AI algorithms analyze customer data to provide fully customized product recommendations, potentially increasing sales conversion rates by up to 15%.
By understanding past purchasing behavior and browsing history, AI can suggest items that customers are more likely to buy.
An example: After a customer purchases a tent on an outdoor equipment website, the AI assistant suggests related products such as sleeping bags and portable stoves, enhancing the shopping experience – and increasing the likelihood of more purchases.
Nowadays, advanced AI agents are capable of handling more sophisticated customer service tasks, such as dispute resolution or technical support, with a level of nuance and understanding that even exceeds that of human agents.
We’re past chatbots now into full virtual agent territory, which can lead to a 40% reduction in the time it takes to resolve complex issues.
An example: A customer is having trouble setting up a product. A virtual agent like Lindy guides them through the process step by step, asking questions to diagnose the issue and providing tailored advice based on the responses.
Sentiment analysis tools evaluate customer feedback, reviews, and social media mentions to gauge overall sentiment towards a brand or product.
This type of AI application can identify trends in customer satisfaction, potentially improving customer retention rates by up to 25%.
An example: After a product launch, sentiment analysis reveals a disturbing trend of negative feedback regarding a specific feature. The company quickly addresses this in an update – demonstrating responsiveness and on-their-feet thinking.
Self-service platforms powered by AI allow customers to find answers and resolve issues on their own, reducing the need for direct interaction with customer service representatives by up to 70%.
This not only improves efficiency but also caters to the customers' preference for finding quick solutions on their own.
An example: A customer visits a FAQ section where an AI assistant offers dynamic, personalized guidance based on their questions, leading them directly to the information they need without navigating through irrelevant, boring content.
Predictive AI analyzes behavioral data to anticipate customer needs or issues before they arise – a massive boost to customer satisfaction by providing proactive solutions.
Implementing predictive customer service can increase customer lifetime value by identifying and addressing potential problems before they rear their ugly heads.
An example: Based on purchase and browsing history, predictive AI anticipates a customer might have questions about how to use a product feature. Before the customer even reaches out, they get an email with helpful tips and links to tutorial videos.
Facial recognition technology is already live in customer service to provide a seamless and secure verification process, reducing the average handling time for security checks by up to 50%.
An example: A customer contacts their bank for account assistance. Instead of going through a long and drawn-out verification process, they’re quickly authenticated through a facial recognition system integrated with AI, allowing the agent to go forward with the request immediately.
AI-powered translation services enable businesses to offer customer support in multiple languages, breaking down barriers and expanding their global reach.
This can lead to a 20% increase in customer satisfaction scores by catering to non-English speaking customers in their native language.
An example: A non-English speaking customer sends a support request in their native language. Lindy's AI instantly understands more than 50 languages and is able to reply using any of them.
AI tools can track a customer's journey across touchpoints, providing insights into behavior and preferences.
This information helps businesses optimize the customer experience at every stage, potentially increasing customer engagement by up to 30%.
An example: AI analysis of customer journey data reveals that users frequently drop off at a particular stage of the online checkout process. The business uses this insight to simplify that step, resulting in higher completion rates.
After a support conversation, AI can summarize the discussion, highlighting key points and agreed-upon actions. This feature saves time and ensures both customer and support agent have a clear record of the interaction, improving follow-up accuracy by up to 40%.
An example: Following a detailed support chat, Lindy provides a concise summary that includes the customer's issue, the solution provided, and any follow-up actions required. This summary is automatically added to the customer's file for quick reference.
When it comes to AI-powered customer service tools, you have plenty of options to choose from.
Here are our top 10:
Want to learn more? Read our in-depth article.
AI-powered chatbots and virtual agents can handle a wide range of basic customer questions. Things like account inquiries, order status updates, product details, store locations and hours of operation. More advanced AI systems are also able to handle complex inquiries, make recommendations based on customer profiles and even complete simple transactions.
The accuracy of an AI system depends on how much data it has been trained on and the quality of that data. Chatbots trained on a large volume of high-quality conversational data, especially data from your own business, will give the most accurate responses. But no AI system is 100% accurate, especially right out of the box. Regular monitoring, testing and re-training are absolutely necessary.
AI will not replace human agents completely, but it will significantly augment and enhance the human workforce. AI chatbots and virtual agents handle basic, repetitive questions so human agents can focus on more nuanced, complex issues. This allows businesses to redeploy human agents into roles that provide more value to both customers and the company.
The cost of an AI chatbot can vary greatly depending on the complexity and capabilities of the system. Basic chatbots with limited features can start around $30-$50 per month. More advanced AI chatbots with natural language processing, contextual awareness and integration with business systems may cost between $100 to $1500 per month or more, depending on the features. Some companies also charge depending on usage volume.
You don't have to be a Fortune 500 company to start taking advantage of AI in your customer service, as these examples of AI in customer support clearly show.
With so many options for integrating AI into your support workflows, any business can find ways to leverage the capabilities of AI.
Start small if needed – even using AI for basic tasks like categorizing support tickets can save you time and provide a better experience for your customers.
Remember: The more you tinker, the more potential there is to discover!
