11 AI customer service examples 2024

Our gallery of 300+ templates can bring teams together at any stage of development. In a use case, scenarios are the sequence of actions customers take when using a system and the flow of effects from that interaction. You can foun additiona information about ai customer service and artificial intelligence and NLP. A user approaches the system, enters the right inputs, and your system helps them reach their goals. Actors generally refer to users and customers but can apply to any outside force that engages with your system. Your actor needs well-defined behaviors explaining how and why actors use your system.

Chatbots can use text, as well as images, videos, and GIFs for a more interactive customer experience and turn the onboarding into a conversation instead of a dry guide. So, you can save some time for your customer success manager and delight clients by introducing bots that help shoppers get to know your system straight from your website or app. Bots will take all the necessary details from your client, process the return request, and answer any questions related to your company’s ecommerce return policy. Chatbots have revolutionized various industries, offering versatile and efficient solutions to businesses while continuously enhancing customer engagement. Deploying chatbots on your website as well as bots for WhatsApp and other platforms can help different industries to streamline some of the processes.

Bots are taking over social media marketing as they allow consumers to engage with them in terms of customer service, and transactional engagements. Customers prefer prompt actions delivered by chatbots fueled with artificial intelligence for better customer engagement. Chatbots can engage with your customers with immediate responses and increase customer satisfaction, which makes them happy to retain your brand. Businesses are constantly seeking innovative solutions to meet evolving customer demands and streamline operations.

With this knowledge, they may concentrate on resolving the problem to lower complaints and raise client happiness. These connectors index your application data so you’re always surfacing the latest information to your users. You can witness the same when performing software troubleshooting, setting up and configuring the hardware, looking for debugging assistance and suggesting code optimizations. More example is seen in its ability to summarise product manuals and documentation to answer the query on specific information about the technical product. We will show you how to build a knowledge base (public or private) in minutes.

When customers post reviews about your business’s customer service online, ChatGPT could be trained to respond to those reviews appropriately so that reviews never go unanswered. Much like a human customer service agent would deal with reviews, ChatGPT can thank customers for their contributions or apologize for mistakes. With Sprinklr’s user-friendly platform, you can confidently deliver personalized and efficient customer service Chat GPT experiences regardless of your technical expertise. Natural language understanding (NLU) is a branch of machine learning that can decode customer intent for agent support. It delves into the subtleties of customer language to provide a deeper comprehension of the customer’s intent and sentiment. For example, a telecommunications company uses machine learning to analyze historical data and predict potential network issues.

Bots can also track the package shipment for your shopper to keep them updated on where their order is and when it will get to them. All the customer needs to do is go onto the company’s website or Facebook page and enter their product’s shipping ID. Every customer wants to feel special and that the offer you’re sending is personalized to them. Everyone who has ever tried smart AI voice assistants, such as Alexa, Google Home, or Siri knows that it’s so much more convenient to use voice assistance than to type your questions or commands. Speaking of generating leads—here’s a little more about that chatbot use case.

Google named a leader in the Forrester Wave: AI/ML Platforms, Q3 2024

Chatbots can help physicians, patients, and nurses with better organization of a patient’s pathway to a healthy life. Nothing can replace a real doctor’s consultation, but virtual assistants can help with medication management and scheduling appointments. Another example of a chatbot use case on social media is Lyft which enabled its clients to order a ride straight from Facebook Messenger or Slack. Also, Accenture research shows that digital users prefer messaging platforms with a text and voice-based interface. Macy’s is another company that has found a unique way to incorporate AI into its customer service offerings.

As many people need internet, TV, or phone service to work and live their daily lives, being able to receive quick help whenever an issue arises is critical. A customer can simply text their issue, and the bot uses language processing to bring the customer the best solution. Regardless of how effective it is, a chatbot can’t replace your human agents as they possess emotional intelligence and are better at diffusing strenuous situations. Evoque recognizes this, and initiates support queries with chatbots that are built to determine the customer need and transfer the case to a corresponding rep. Qualify leads, book meetings, provide customer support, and scale your one-to-one conversations — all with AI-powered chatbots.

They offer a diverse range of applications that streamline support processes, and optimize operations. In today’s digital era, chatbots have significantly impacted the banking industry, offering a myriad of innovative and convenient use cases that optimize operational efficiency. These AI-powered virtual assistants have become valuable assets, streamlining various aspects of banking services and improving interactions between customers and financial institutions. Chatbots are computer programs designed to interact with users through conversational interfaces. They are versatile tools applicable to various industries and business functions, such as customer service, sales, marketing, and internal process automation. These numerous use cases for chatbots have contributed to their widespread adoption as virtual assistants.

The regulations from the government have also been generated, leading to businesses providing complete information about the method of data usage, storage and further actions. The businesses balance personalization and privacy by adhering to the regulatory guidelines and maintaining data anonymization. Hopefully, ChatGPT will progress to a stage where it can offer highly individualized answers to customers, no matter what their issue is. Of course, complex cases will always have to be escalated to the people on your team, but ChatGPT should be able to make basic changes such as account updates or amending bookings. ChatGPT only accepts input in text form with limited characters, making it less than suitable for some forms of customer service.

The chatbot can also book an appointment for the patient straight from the chat. A patient can open the chat window and self-schedule a visit with their doctor using a bot. Just remember that the chatbot needs to be connected to your calendar to give the right dates and times for appointments. After they schedule an appointment, the bot can send a calendar invitation for the patient to remember about the visit. And no matter how many employees you have, they will never be able to achieve that on such a big scale. No wonder the voice assistance users in the US alone reached over 120 million in 2021.

Having understood the use cases of machine learning in customer service, let’s now examine some brands that are using machine learning to grow. Conversational AI leverages natural language processing (NLP) algorithms to understand and interpret human language, allowing it to engage in customer conversations to simulate human interaction. It can answer frequently asked questions, provide product information, assist with troubleshooting and even process simple transactions. A robust and well-organized knowledge base is indispensable to harnessing the full potential of machine learning in customer service.

Opinion mining can also be used to analyze public competitor reviews or scour social media channels for mentions or relevant hashtags. This AI sentiment analysis can determine everything from the tone of X mentions to common complaints in negative reviews to common themes in positive reviews. You deploy AI to crawl recent survey results with open-ended responses to quickly identify trends in user sentiment, giving you data-driven insights into new product feature ideas.

Examples of AI in Customer Service (From Companies That Do It Right)

Rather than defining processes for every specific task, you can build these generative AI bots once and deploy them across multiple channels, such as mobile apps and websites. This means that customers can get the answers they need, regardless of how they interact with your organization. Using the Dialogflow Messaging Client, you can then easily integrate the agent into your website, business or messaging apps, and contact center stack. This provides a quick and easy way to divert a large number of support calls to self-service, with relatively low investment and high customer satisfaction. At the end of the day, ChatGPT is a robot and although its conversational style is human-like, it still lacks the emotional touch. This absence of personal feeling may drive already frustrated and upset customers to become even more disillusioned with your brand, so you should always be careful when deploying chatbot technology.

As technology continues to evolve and businesses recognize the value of chatbots, their popularity is predicted to rise even further. Gartner predicts that by 2027, approximately 25% of organizations will have chatbots as their main customer service channel. With their increasing adoption and advancements in AI technologies, chatbots are poised to play an even more critical role in shaping the future of customer engagement and service delivery. Embracing chatbots today means staying ahead of the curve and unlocking new opportunities for growth and success in the ever-evolving digital landscape. Chatbots for customer service can help businesses engage clients by answering FAQs and delivering context to conversations. Businesses can save customer support costs by speeding up response times and improving first response time which boosts user experience.

The new GPT variant is much more proficient at simulating human language and is able to respond to more natural user input. It also has an extensive knowledge base and is able to recall previous conversation points and even call out a person for lying. Stick with us the whole way to discover use cases of ChatGPT for customer service, its limitations, and unique Chat GPT prompts for customer service leaders. You’ll also learn how to completely reinvigorate your CSAT responses using ChatGPT.

Multilingual support

This chatbot use case also includes the bot helping patients by practicing cognitive behavioral therapy with them. But, you should remember that bots are an addition to the mental health professionals, not a replacement for them. But if the bot recognizes that the symptoms could mean something serious, they can encourage the patient to see a doctor for some check-ups.

However, they can be difficult to find, and customers often don’t have the time or patience to search for them. H&M is a fashion retailer brand that utilizes virtual assistants as AI customer care to help customers find clothing items and answer style-related questions. The virtual assistant handles multiple customers simultaneously and provides instant responses and recommendations on fashion-based topics. The shopping seasons have seen maximum benefits where they no longer need to wait for human assistants to get free.

Or maybe you just need a bot to let people know when will the customer support team be available next. Vercel’s story aligns with the broader trends identified in the McKinsey survey, where organizations report both cost reductions and revenue increases in business units deploying gen AI. Our experience demonstrates that when implemented thoughtfully, AI can be a powerful tool for enhancing customer experience while optimizing operational efficiency. Whether you’re an AI-first company or looking to enhance existing products, Vercel provides the tools and knowledge to help you revolutionize your customer support and beyond with AI. Customer analytic software is used to create visual dashboards that update in real-time. Zendesk’s customer analytic software comes with pre-built dashboards that are great for a high-level look at your customer data, and they can be shared with agents and administrators.

This ensures a smoother resolution process and helps your business avoid further escalations. For instance, a scenario where a customer asks, «Where is my order? It was supposed to reach me yesterday.» The AI can sense from the tone that the sentiment is negative and the customer is displeased. AI simplifies workflows, allowing your team to focus on high-value tasks by introducing streamlined tools and automation. If you are looking for real life examples of conversational commerce you can read our Top 5 Conversational Commerce Examples & Success Stories article. It involves monitoring and recording all financial transactions incurred by an individual or organization. This process helps individuals and businesses manage their budgets, track spending patterns, and make informed financial decisions.

Self-service portals powered by AI empower customers to find solutions to their problems independently. These portals often include knowledge bases, FAQs, and troubleshooting guides. AI algorithms help customers search for relevant information more efficiently by understanding their queries and providing relevant content.

AI technology can be used to reduce friction at nearly any point in the customer journey. Utilize Sprout’s Instagram integration to create, schedule, publish and engage with posts. Ronnie Gomez is a Content Strategist at Sprout Social where she writes to help social professionals learn and grow at every stage of their careers.

AI-based customer service has improved significantly from the days when agents were hoping between windows to get data and knowledge base content. Now agents have less work to do thanks to the integration of AI in customer service tools. To achieve the promise of AI-enabled customer service, companies can match the reimagined vision for engagement across all customer touchpoints to the appropriate AI-powered tools, core technology, and data. For enhanced customer satisfaction and faster troubleshooting without involving the customer service reps, chatbots provide pre-made troubleshooting guides to specific technical questions. Being present in social media platforms where customers spend time is important. However, knowing which social media channels a chatbot vendor offers is important to align your selection with your needs.

However, you can also note internal errors that cause a system to break down or unintended ways systems can reach goals. Use cases show all the ways a system functions when trying to reach goals, but a scenario only depicts one example. Since so many of its uses are continuing to evolve, some of these risks will also continue decreasing over time as implementation complexities get ironed out.

When your customer service representatives are unavailable, the chatbot will take over. It can provide answers to questions and links to resources for further information. Today, many bots have sentiment analysis customer service use cases tools, like natural language processing, that help them interpret customer responses. Using chatbots as an example, you can automatically respond to a customer‘s live chat message within seconds.

HubSpot chatbot displays a friendly message letting customers know that it’s there to help. But, these aren’t all the ways you can use your bots as there are hundreds of those depending on your company’s needs. This way, you will get more usage out of it and have more tasks taken off your shoulders. And, in the long run, you will be much happier with your investment seeing the great results that the bot brings your company. Another great chatbot use case in banking is that they can track users’ expenses and create reports from them. This is one of the chatbot use cases in banking that helps your bank be transparent, and your clients stay on top of their finances.

The data used here is previous watches, preferences and behavior on the platform. The Netflix recommendation algorithm helps to quickly discover the content of their taste. Customer satisfaction is visible in longer subscription retention and content consumption.

By analyzing resolved tickets, we identified areas for enhancement in documentation, product interface, and the product itself. We also created a data flywheel, where each interaction improved the AI’s performance, leading to better outcomes over time and a virtuous cycle of improvement. Data-driven insights are crucial for identifying trends, measuring performance‌ and improving processes.

Do you need a customer service chatbot?

AI affects customer service by allowing support teams to automate simple resolutions, address tickets more efficiently, and use machine learning to gain insights about customer issues. While this process doesn’t directly address users or resolve active issues, it can still be an incredibly useful tool for identifying common friction points for customers. Optimum has an SMS chatbot for customers with support questions, giving users quick access to 24/7 support.

When your team gets comfortable with the flow of AI you can start using it on a larger scale. Service leaders are facing a skills gap because AI, particularly generative AI, which is a relatively young discipline. For instance, according to many leaders, their team lacks the expertise necessary to handle AI. The fact that the digital assistant could understand and respond to over 1000 unique customer intentions is a testament to the power of AI.

A key feature of our implementation was the constant presence of a clear «Create Case» option. At every step, customers had the ability to opt out of the AI experience and connect with a human support engineer, ensuring they always felt in control of their support experience. This approach empowered customers, created a valuable feedback loop, and enabled rapid improvements. Instead of deploying a basic AI chatbot quickly, we developed a sophisticated, customer-centric AI solution that respects customer preferences while leveraging advanced technology. Forward-thinking customer care leaders are increasingly using AI to scale their efforts without overwhelming agents.

Behind every seemingly effortless ticket resolution is a pressure-tested customer service case management strategy that allows teams to streamline efforts and improve outcomes. It’s more than just a framework—it’s the backbone of delivering a seamless customer experience. Data analytics is used in customer service analytics to gather, examine, analyze, and interpret customer interaction data to increase service quality, spot trends, and improve the overall customer experience. Features like Call Companion help to supplement voice interactions and make it easier and faster for customers to get answers. This can help accelerate the time it takes to resolve service and support calls, and everything can be handled by a virtual agent from start to finish.

Watch this demo from our Next ’23 session to see this useful feature in action. Instead of hard-coding information, you only need to point the agent at the relevant information source. You can start with a domain name, a storage location, or upload documents — and we take care of the rest. Behind the scenes, we parse this information and create a gen AI agent capable of having a natural conversation about that content with customers. We’ll be adding real-time live translation soon, so an agent and a customer can talk or chat in two different languages, through simultaneous, seamless AI-powered translation.

Based on Gartner’s research, there is a projected 40% increase in the adoption of chatbot technology, with 38% of organizations planning to implement chatbots within the next two years. Join Master of Code on this journey to discover the boundless potential of chatbots and how they are reshaping the way we interact with technology and information. Chatbots and virtual assistants are AI-powered solutions that enable businesses to provide immediate and efficient customer support. They can handle routine inquiries, such as frequently asked questions, account inquiries, or basic troubleshooting. Using natural language processing (NLP) algorithms, chatbots can understand and respond to customer queries conversationally, making the interaction more human-like.

Conversational IVR systems leverage machine learning algorithms for natural language understanding (NLU), enabling them to comprehend and interpret spoken language. By analyzing callers’ speech patterns, accents and vocabulary, the IVR systems can accurately discern their intent and extract relevant information from their utterances. This proficiency in NLU empowers the IVR systems to effectively route calls, provide information and execute tasks based on caller requests.

• Whether it’s providing real-time assistance, automating repetitive tasks, or offering personalized recommendations, chatbots continue to redefine the future of customer engagement and service delivery.
• It allows machines to understand and interpret human language, enabling chatbots and virtual assistants to engage in meaningful customer conversations.
• To drive a personalized experience, servicing channels are supported by AI-powered decision making, including speech and sentiment analytics to enable automated intent recognition and resolution.
• However, knowing which social media channels a chatbot vendor offers is important to align your selection with your needs.
• The Customer Satisfaction Score (CSAT) measures the satisfaction level of service or a particular interaction with clients.

When implemented properly, using AI in customer service can dramatically influence how your team connects with and serves your customers. According to HubSpot’s annual State of Service report, 86% of leaders say that AI will completely transform the experience that customers get with their company. Companies that are using these technologies are often quicker to respond to my needs and focused on delivering a helpful outcome. As someone who loathes spending hours on the phone just to reach a customer service rep that can fix my issue, I can see a ton of value in implementing more AI solutions. McKinsey’s latest AI survey shows 65% of organizations now regularly use AI — nearly double from just ten months ago, with many using it to increase efficiency in critical areas like customer support.

It has replaced the need for translators with a multilingual chatbot that assists guests and hosts in booking inquiries and support requests. The easy and accurate interpretability in multiple languages has offered the marketplace of a complete world to Airbnb effortlessly. The different techniques being utilized to enable the handling of complex and technical inquiries. The knowledge base integration provides data for reference, and semantic understanding guides the AI to the context of the question.

All that time can be poured back into resolving cases and creating better customer experiences. Google FI is a mobile network operator that uses chatbots to serve its customers. The response time is lower, and the incorporation of chatbots has increased the efficiency of human employees due to the lack of need to focus on such automatable tasks. The customer feedback has also been positive on the Google Fi chatbot, appreciating it for quick and accurate responses.

The data can also tell a story of how a support organization is functioning, leading to optimization for ideal customer support or departmental budgeting. Providing an AI-powered 24/7 customer service chat can help handle most queries and transfer customers to live agents when needed. Advanced natural language understanding (NLU) technology detects a customer’s native language and translates conversations in real time. For example, if customers from Japan and Spain contact support simultaneously, your AI system instantly recognises and translates their languages, ensuring efficient support regardless of language.

As you integrate AI into your service organisation, make sure to explain to your personnel how it will increase productivity while still needing their human talents to deliver a first-rate customer experience. Customers like AI as it provides them with personalised answers within seconds. It is just like a virtual assistant who understands both the needs and the preferences of your consumers. It makes things easier for them as they don’t need to find many things manually on the website. They can just communicate with the AI bot and find their answers immediately within the chat. With the reducing attention spans the consumers are now demanding quick solutions to their queries.

Bots have been used widely across different business functions like customer service, sales, and marketing. With REVE Chat, start a free trial of advanced customer support software and start delivering great experiences to customers. Your customer can interact with the chatbot using natural language, making the experience intuitive and user-friendly. Appointment scheduling chatbots reduce the need for manual intervention in appointment booking, saving time for both customers and businesses. Chatbots significantly boost user engagement on these popular social websites and communicate with customers through live chat platforms like Facebook Messenger.

The stepwise action should be to introduce yourself to different generative AI models and then choose the right one that suits the necessities. Make life easier for your customers, your agents and yourself with Sprinklr’s all-in-one contact center platform. Customer analytics helps businesses deeply understand their audience to make smarter business decisions and improve CX.

The EVA bot has been configured to handle queries on more than 7,500 FAQs, along with information on the bank’s products and services. With an accuracy level of over 85% and uptime of 99.9%, EVA is boosting customer experience https://chat.openai.com/ using various conversational interfaces. Bringing AI into customer service processes can be a big undertaking, but it can also pay dividends in issue resolution efficiency, customer satisfaction, and even customer retention.

Part of great customer service is understanding what customers mean, rather than simply focusing on what they say. ChatGPT was not strictly built with customer service in mind, but its ability to generate human-like responses and creatively answer questions has made it of interest to customer service teams. For many typical customer inquiries, ChatGPT will be able to find a coherent answer – if the information is already available somewhere. Fortunately, a solution exists to automate the repetitive tasks that consume customer service agents’ valuable time and patience. Machine learning in customer service is gaining widespread popularity because it achieves the coveted balance of low cost and high efficiency.

It tries to read a customer’s state of mind more like a human to respond in kind. Integrating machine learning into customer service can be challenging for many businesses due to the need for specialized coding skills and deep AI expertise. The scarcity of AI talent and high hiring costs further compound the problem. Zendesk has long been committed to delivering trustworthy products to our customers and their users. We believe that trust is at the core of all our interactions with our customers. From customer satisfaction to resolution time, these are the key customer service metrics that measure performance and drive revenue.