10 Must-Know Customer Service Chatbot Examples for Business Owners

Quick Summary

We've rounded up 10 interesting customer service chatbot examples, used by different companies. Jortt and Ricardo, both built with Wonderchat, are among the standouts. You’ll also see great examples like Amtrak’s Nuance-powered bot and Lyft’s chatbot built with Claude.

Looking for Real-World Chatbot Examples That Work?

Customer service is now under INTENSE pressure to be always on.

According to a HubSpot study, 90% of customers rate an “immediate” response as important or very important when they have a support question. One of the few realistic ways to keep up with this demand is by using customer service chatbots.

The problem is, most advice stops at “use a chatbot” without showing what good actually looks like.

That is why, in this Wonderchat guide, you will see 10 customer service chatbot examples, how they were built, what each one does well, and how to adapt those ideas to your own business.

But before we dive in…

Why Listen to Us?

At Wonderchat, we don’t just talk about chatbots; we build them. Our no-code platform helps businesses create AI-powered chatbots that deliver real results in minutes. With experience serving businesses across different industries, we understand what works (and what doesn’t) when it comes to customer service automation. 

What Is a Customer Service Chatbot?

A customer service chatbot is an AI-powered tool that helps businesses handle customer inquiries through automated, real-time conversations. These bots are typically deployed on websites, apps, and messaging platforms to answer FAQs, resolve issues, and route complex queries to human agents.

They are powered by AI models that can be configured by your team to understand and respond to customer input. This helps reduce wait times and support costs. Many advanced bots can access customer data, personalize responses, and even process returns or cancellations. 

Why Customer Service Chatbots Matter

For businesses, customer service chatbots are a way to offer 24/7 support, improve satisfaction, and free up human teams for higher-value tasks.

• 24/7 Support Without Extra Staff: Chatbots provide round-the-clock assistance, ensuring customers get instant responses even outside business hours, without increasing headcount or payroll costs.

• Faster Response Times: By instantly answering common questions, chatbots reduce wait times and improve customer satisfaction, especially during peak hours or product launches.

• Scales Effortlessly With Growth: As customer volume grows, chatbots handle thousands of conversations simultaneously without compromising service quality or requiring additional agents.

• Reduces Operational Costs: Automating repetitive queries lowers the need for large support teams, saving businesses money on salaries, training, and overhead.

• Improves Agent Productivity: Chatbots handle routine questions, allowing human agents to focus on complex cases and provide better service where it matters most.

10 Best Customer Service Chatbot Examples

1. Jortt – Accounting Software

Jortt, a fast-growing Dutch accounting platform, faced a steady rise in repetitive customer questions, ranging from invoice setup and reconciliation steps to tax rules and plan limitations. These frequent queries were overwhelming their support team, slowing down response times, and making it harder to focus on complex issues.

Chatbot Solution

To streamline support, Jortt implemented “Femke,” an AI assistant powered by Wonderchat, on their help center. Trained on Jortt’s own support articles and knowledge base, the chatbot delivers instant, accurate responses on everything from product features to onboarding steps. It’s embedded directly on their site, ensuring 24/7 availability without adding to support workloads.

Tool Used

Built with Wonderchat, the chatbot pulls content directly from Jortt’s help documentation and handles real-time queries through a no-code interface.

Results

Since its launch, Jortt has managed to resolve 92% of common customer queries, reducing the burden on human agents. It also saved over 10 hours of support time per month, enabling the team to focus on more complex issues and improve their help documentation.

2. Ricardo – E-Commerce Marketplace

Ricardo.ch, Switzerland’s leading online marketplace, faced thousands of help center queries each month, which are mostly repetitive questions about listings, fees, policies, and more. This volume strained their support team and delayed responses to more complex inquiries.

Chatbot Solution

To scale their customer service, Ricardo introduced Lea, a multilingual AI assistant trained on Ricardo’s internal help documentation. This powerful virtual assistant provides instant responses in German, French, Italian, and English, making support accessible to their multilingual customer base. In addition, Lea operates 24/7, efficiently managing thousands of repetitive queries each month. When a request requires human attention, she quickly escalates it to Ricardo’s support team without disrupting the customer experience.

Tool Used

Built with Wonderchat, Lea is fully integrated into Ricardo’s help center, delivering fast, language-appropriate support right where users need it.

Results

Since launch, Lea has resolved over 100,000 queries and now manages more than 10,000 requests monthly. Ricardo’s team has saved over 100 hours of support time, allowing them to focus on higher-value service. With Lea, Ricardo now offers faster, always-on assistance that meets users in their preferred language without compromising quality.

3. Amtrak – Travel Industry

Amtrak faced a massive volume of repetitive customer inquiries, schedule checks, booking changes, fare questions, and station information. Their call centers were overwhelmed, leading to long wait times, rising costs, and customer frustration.

Chatbot Solution

They launched “Julie,” a voice and text virtual assistant powered by Nuance. Accessible via phone or website, Julie guides users through booking and change flows, shares real-time train schedules, provides station info, and explains fare rules. Julie references Amtrak’s own data to ensure accuracy and can seamlessly initiate ticket purchases.

Tool Used

Built with Nuance’s conversational AI and integrated into Amtrak’s existing systems. 

Results

Julie processes 20 million calls annually for Amtrak, successfully resolving 5 million interactions without human intervention. This represents 25% of the company's total inbound call volume and achieves a 54% success rate among customers who engage with the self-service system. The implementation has dramatically reduced call center costs while boosting customer satisfaction by 53%.

4. Lyft – Ride-Hailing Industry

Lyft experienced high volumes of repetitive inquiries from both drivers and riders, such as fare info, policy questions, and navigation assistance. These routine requests flooded support channels and slowed down resolution times.

Chatbot Solution

Lyft partnered with Anthropic to deploy a Claude-powered AI assistant via Amazon Bedrock. The bot handles thousands of user queries daily, accurately answering common questions about account access, ride requirements, and fare calculations. If the bot detects a complex or high-stakes issue like safety concerns, it automatically escalates to human agents for further review.

Tool Used

Anthropic’s Claude, integrated into Lyft’s support flow through Bedrock, combines large-language-model capabilities with smart escalation logic.

Results

Since deployment, the Claude chatbot has helped Lyft resolve average customer service requests 87% faster while also handling thousands of daily requests and seamlessly transferring critical issues to human support. This shift has significantly improved operational efficiency while keeping human oversight for safety-sensitive cases.

5. Vodafone – Telecom Industry

Vodafone’s agents were wasting valuable time manually reviewing customer account histories before each call, leading to longer handling times and inconsistent support across channels.

Chatbot Solution

Vodafone developed an in-house generative AI assistant, an enhanced version of their virtual assistant TOBi. It synthesizes customer billing history, interaction notes, and contract details in real time. Agents type a query and instantly receive a concise summary to guide their responses, streamlining workflows without disrupting operations.

Tool Used

A proprietary generative AI model integrated directly into Vodafone’s internal support platforms.

Results

During pilot deployments, this tool boosted first-time resolution in Portugal from 15% to 60% and lifted online NPS by 14 points to 64. Agents also reported handling queries up to 50% faster and better. All these led to fewer support tickets, improved agent efficiency, and a more consistent customer experience.

6. Comcast – Telecommunications Industry

Comcast agents frequently switched between dashboards and knowledge bases during live chats, costing time and disrupting conversation flow. This led to slower response times and inconsistent customer experiences.

Chatbot Solution

Comcast implemented an internal “Ask Me Anything” large language model assistant that plugs directly into agents’ support interface. The tool monitors ongoing chats, fetches relevant guidance, troubleshooting steps, and policy info, and offers instant suggestions. Agents can insert responses with a click or customize them before sending, simplifying the interaction process.

Tool Used

A bespoke LLM-powered assistant built in-house, trained on Comcast’s internal documentation and support materials.

Results

By integrating the LLM assistant, Comcast reduced internal context-switching delays by around 10%, enabling agents to handle issues faster and maintain a smoother customer dialogue. The result was higher agent efficiency and more consistent support quality.

7. Klarna — Fintech

Klarna faced a surge in customer inquiries regarding payments, refunds, and order status. This volume stretched its support team thin, resulting in long wait times (about 11 minutes per query), and repetitive, low-complexity tasks consumed valuable human resources.

Chatbot Solution

Klarna rolled out a generative AI assistant powered by OpenAI to handle routine customer requests 24/7. The bot guides users through payment schedules, refund status, and transaction details. Complex or sensitive issues are escalated to human agents, ensuring quality for higher-stakes interactions.

Tool Used

Built in-house using OpenAI’s GPT models, deeply integrated with Klarna’s order and payment systems.

Results

In its first month, the AI assistant handled 2.3 million conversations, resolving roughly two-thirds of all inquiries. It cut average wait time from 11 to under 2 minutes, eliminated about 25% of repeated questions, and helped Klarna improve operational efficiency and customer satisfaction.

8. Amazon – E-Commerce & Contact Centers

Amazon handles massive volumes of customer inquiries every day; orders, returns, product info, troubleshooting, all done through chat and voice channels. Traditional support systems struggled with wait times, inconsistent responses, and human-agent limits.

Chatbot Solution

Amazon uses Alexa and Amazon Lex, the conversational AI technology behind it, to power chatbots for voice- and text-based support. Lex enables intent recognition and multi-turn dialogue in contact center bots. Customers can ask Alexa for order status, shipment tracking, and returns info. In the app or on the device, the assistant guides users through solutions smoothly and is programmed to escalate to agents for complex issues via Amazon Connect integration.

Tool Used

Self-built conversational system using Amazon Lex (for NLP and dialogue flows) and Amazon Alexa for voice interaction. It integrates with Amazon Connect and backend systems for real-time responses. 

Results

With Lex, Amazon’s contact centers handle more self-service cases, reducing average call times and wait times by up to 30%, based on usage across AWS customers. Its multi-modal chatbot handles tens of thousands of requests daily and offers seamless transition to live agents when needed. The system enhances scalability and consistency while improving customer satisfaction.

9. Domino’s – “Dom” the Pizza Ordering Chatbot

Domino’s needed a more scalable way to handle the growing number of digital orders and customer service queries, especially during peak hours. They wanted a solution that streamlined ordering while also handling basic support tasks like tracking and store lookup.

Chatbot Solution

Domino’s launched “Dom,” a multichannel ordering assistant available on Facebook Messenger, Google Assistant, Amazon Alexa, and SMS. Customers can reorder their usual, customize a new pizza, track deliveries, and find the nearest store, all without needing to speak to a human.

Tool Used

Dom was built using a mix of in-house development and integrations with platforms like Facebook Messenger, paired with NLP capabilities from services like Dialogflow and AWS.

Results

Domino’s attributed a significant increase in digital orders to Dom’s convenience, with over 70% of U.S. sales now coming through digital channels. The chatbot also reduced pressure on call centers and improved order accuracy.

10. 1-800-Flowers – “GWYN” (Gifts When You Need)

1-800-Flowers wanted to simplify gift buying for online customers who often felt overwhelmed by too many options. They needed a chatbot that could guide people through product discovery, even if they weren’t sure what to buy.

Chatbot Solution

They partnered with IBM to create GWYN, short for “Gifts When You Need.” The chatbot is accessible via their website and Facebook Messenger. GWYN asks users questions about the occasion, recipient, and preferences, then recommends curated gift options with direct links to purchase.

Tool Used

GWYN runs on IBM Watson’s natural language processing engine, allowing it to interpret conversational inputs and improve with continued interactions.

Results

Customers who interacted with GWYN were more likely to complete purchases, and reported a better shopping experience overall. The use of AI for guided selling helped 1-800-Flowers differentiate itself in a crowded e-commerce market.

Start Building Smarter Customer Support Today

Customer service chatbots aren’t just a trend, they’re transforming how brands interact with customers. From answering FAQs to streamlining purchases, these tools save time and create better experiences. 

Ready to implement your own? With Wonderchat’s no-code platform, you can launch an AI-powered chatbot in minutes. 

Feel free to view a Wonderchat demo or start for free today and elevate your customer support!

FAQs

How do I choose the right customer service chatbot for my business?

It helps to start with the basics: what do you actually want a customer service chatbot to handle? Quick FAQs, order updates, or full-on troubleshooting? Once you know that, it’s easier to compare chatbots for customer service based on setup time, integrations, and cost.

The “best customer service chatbot” for you is the one that solves your biggest headaches without adding new ones. Tools like Wonderchat keep things simple, and many teams consider it one of the best customer service chatbots because you can get up and running without a developer.

What are the most useful chatbot use cases for customer service?

There are plenty of strong chatbot use cases for customer service, but the most popular ones usually involve repetitive questions. Think order tracking, password resets, account updates, or routing customers to the right place. These customer service chatbot use cases save a lot of time because they reduce ticket volume while keeping customers happy.

If you need inspiration, you can always look at some customer service bot examples we've provided in this guide.

How do I set up a chatbot for customer service on my website?

If you just want a quick, reliable customer support chatbot solution, go for a no-code option. With Wonderchat, you can build a customer service chatbot solution using your existing FAQs or help docs, then drop a small snippet into your site.

A good customer support chatbot solution for websites should give you full control over tone, greeting messages, and when the bot hands off to a human. Once your chatbot for customer service is live, you can tweak it based on real customer conversations.

How do I improve my customer service bot’s answers?

The quality of your customer service bot comes down to the quality of your content.

Make sure your FAQs and help articles are clear, updated, and easy to understand. Test the bot regularly and update anything that sounds off.

Some teams build a small library of chatbot responses examples to guide improvements. One advantage of platforms like Wonderchat is that your updates instantly improve all your customer service bots without extra work.

How do I know if my customer service chatbots are performing well?

Check how many conversations your customer service chatbots handle without a human jumping in. Look at response times, customer satisfaction, and whether ticket volume drops after adding automation.

It’s also worth comparing your numbers to other tools claiming to be the best customer service bots. Wonderchat gives you real-time insights into what customers ask and where the bot gets stuck, so you can keep improving your chatbots for customer service instead of guessing.

What are some e-commerce customer service chatbot examples?

Some of the best e-commerce customer service chatbot examples include bots that track orders, manage returns, share size guides, or recommend products.

Many stores also use customer service chatbot examples that handle shipping questions or low-stock alerts. If you browse ai chatbot examples in retail, you’ll notice how quickly they answer common questions.

With Wonderchat, you can build similar experiences using your own product info and policies—no custom development required.

Why do many teams choose Wonderchat over building their own chatbot?

Building a customer service chatbot yourself sounds exciting until you hit maintenance, updates, and edge cases. Wonderchat takes that off your plate by giving you proven customer service bot examples and flexible flows you can adjust to your brand. You can still customise everything, but without the stress of managing a full engineering project.

For many small and mid-sized teams looking for the best customer service bots, it’s simply the fastest path to a reliable setup.

Are there best practices for improving customer service chatbot use cases?

Yes — and they apply across most customer service chatbot use cases. Keep the bot’s greeting simple, make the handoff to humans clear, and test the bot with real customer questions before going live.

Looking at customer service bot examples from businesses similar to yours helps you spot gaps quickly.

Can a customer service bot really replace human agents?

Not fully, and that’s usually not the goal. A customer service bot handles the repetitive stuff so your team can focus on the conversations that actually require a human. When you look at the best chatbot customer service example, it’s usually a bot that supports agents—not replaces them. The ideal setup is a mix of automation and human empathy.