6 Best Chatbot Examples in 2025 (E-commerce & Support)

Many people have encountered chatbots that don't meet expectations. While the promise of AI is smooth, intelligent conversations, some users experience interactions that end in a loop of "I'm sorry, I don't understand." However, many bots are genuinely useful, moving beyond simple scripts to have helpful conversations.

This post highlights six real-world chatbot examples in customer service, sales, and e-commerce. The selection is based on testing and analysis of what makes a bot a valuable part of a team.

What makes a great chatbot example?

A modern AI chatbot isn't just a decision tree with pre-written answers. Chatbot technology has evolved from simple, rule-based bots that have difficulty with off-script questions. Today's conversational AI understands natural language, remembers context, and solves problems. Effective chatbots guide users to solutions, anticipate needs, and learn from interactions, as shown in the graphic below.

This represents a shift from thinking about a chatbot as a rigid tool to seeing it as an "AI teammate." A well-designed bot can function like an AI teammate that understands your business, rather than a tool that requires constant maintenance. This is the idea behind platforms like eesel AI, which are designed to be invited into existing tools to learn on the job, just like a person would. These advanced bots can understand the context of a conversation, connect to business tools like help desks and Shopify, and personalize every interaction to be helpful.

How we selected the best chatbot examples

To put this list together, the focus was on what contributes to a good customer experience. Here’s the criteria used:

• Ease of Setup: How quickly can a team get started without a squad of engineers? The best tools don't require months of complicated setup. You should be able to get up and running fast.

• Quality of Conversation: Does it actually sound human? Can it handle curveball questions and complex requests, or does it fold under pressure and leave users frustrated?

• Integration Power: A chatbot shouldn't live on an island. How well does it plug into the tools you already use every day, like Zendesk, Shopify, or Slack? A great bot works where your team and your knowledge already are.

• Real-World Impact: At the end of the day, does it actually make a difference? We looked for clear proof that these bots save time, increase sales, or make customers happier. It's all about tangible results.

A glance at the best chatbot examples for 2025

Here is a quick summary of the top chatbots we reviewed.

Chatbot	Best For	Key Feature	Pricing Model
eesel AI	Teams wanting an AI teammate, not a tool	Learns from past tickets & integrates instantly	Starts at $299/mo for 1,000 interactions
DevRev Turing AI	Unifying support and product development	AI agents that automate L1 support and tasks	Starts at $19.99/user/month
Lemonade's Maya	Simplifying complex sales processes	Friendly, guided insurance quoting	N/A (Internal Tool)
Domino's Dom	Effortless e-commerce ordering	Re-ordering favorites via messaging apps	N/A (Internal Tool)
Bank of America's Erica	Personalized financial management	Proactive insights and account management	N/A (Internal Tool)
Sephora Kik Bot	Personalized retail and product discovery	In-chat makeup tutorials & recommendations	N/A (Internal Tool)

A closer look at six leading chatbot examples

Now let's dive deeper into what makes each of these chatbots stand out. Each one excels in a different area, from customer support automation to frictionless sales.

1. eesel AI

First up is eesel AI, which stands out because it’s positioned as an AI teammate platform. You don't build it; you invite it into your company. It immediately gets to work learning from your past support tickets, help center articles, and internal docs. It shows up ready to help.

Pros and Cons: A key advantage of eesel AI is its ease of setup. It can go live in minutes without developer assistance. It starts out in a human-in-the-loop mode as an AI Copilot, drafting replies for your team to review and approve. This reduces the risk of incorrect responses to customers. It learns from your team's edits and feedback, getting smarter with every interaction. It also unifies sales and support, with deep integrations into e-commerce platforms like Shopify. The main thing to consider is that its performance scales with the quality of your existing knowledge. While it can learn from scratch, it performs best when it has good historical data to analyze.

Pricing:

• Team: $299/month for 1,000 interactions.

• Business: $799/month for 3,000 interactions, which adds the ability to train on past tickets and use AI actions.

• Custom: Custom plans are available for larger teams with unlimited interactions.

2. DevRev

DevRev's platform, which they call "Computer," is an AI teammate built to bridge the gap between customer support, product, and engineering. Its focus is on pulling data from different places (emails, tickets, spreadsheets) to create a single source of truth for the entire company.

Pros and Cons: DevRev is effective at spotting patterns in support tickets and using its Turing AI to automate L1 support and help build out your knowledge base. This data-driven approach is useful for helping product teams prioritize bug fixes and feature requests based on what customers are actually saying. Because it’s part of a larger platform, it may have more features than a team needs if they are only looking for a simple chat agent.

Pricing:

• The Support Starter plan begins at $19.99/user/month. They also offer Pro and Ultimate plans, but you'll need to get a custom quote for those.

3. Lemonade's Maya

Maya is an example of a chatbot that’s hyper-focused on a specific sales job. It takes the traditionally complex process of getting an insurance quote and turns it into a quick, friendly, and conversational experience.

Pros and Cons: Maya's design focuses on a narrow scope and a conversational personality. As Lemonade's AI bot, Maya helps users get insured. It builds trust by feeling like you're talking to a helpful person, not a cold machine, and guides you through the process without any friction. A key point is that it's an internal tool built by Lemonade and not available for purchase. However, it's a useful case study for how a custom-built sales bot can automate a sales funnel and make it feel effortless for the customer.

Pricing:

• Not applicable (internal tool).

4. Domino's Dom

Dom is a classic example of a transactional chatbot that works. It lets customers place and track pizza orders directly through platforms like Facebook Messenger, so you never have to open an app or a website.

Pros and Cons: Dom offers convenience to customers. It meets customers where they already are, on the messaging apps they use all day. This makes re-ordering a pizza a simple process. This strategy has been a driver of mobile order volume for Domino's. It's not a general-purpose customer service bot; it is a highly specialized sales channel designed for one thing: selling pizzas as efficiently as possible.

Pricing:

• Not applicable (internal tool).

5. Bank of America's Erica

Erica is a more advanced AI financial assistant that goes beyond simple tasks like checking your balance. It lives inside the Bank of America mobile app and offers proactive insights, spending analysis, and personalized guidance to millions of customers.

Pros and Cons: Erica provides tangible value by helping people manage their money more effectively. It can alert you to a low balance, show you where you're spending the most, and answer complex questions. Its deep integration with the bank's backend systems allows it to handle billions of interactions. The biggest challenge for other businesses looking to replicate this is the investment required. Building an AI with this level of security, personalization, and integration is a large project.

Pricing:

• Not applicable (internal tool).

6. Sephora's Kik Bot

The Sephora bot on the messaging app Kik was a pioneer in conversational commerce for the beauty world. It acts like a virtual beauty advisor, offering personalized product recommendations, makeup tips, and reviews, all within a chat conversation.

Pros and Cons: This bot is effective at engaging a younger audience by creating an interactive and highly visual shopping experience. It uses quizzes and tutorials to make discovering new products fun, which helps drive higher conversion rates than a standard e-commerce site. Its success, however, is tied to the Kik platform. While it was a huge hit when it launched, Kik has a more niche audience today, making this a powerful but platform-dependent example.

Pricing:

• Not applicable (internal tool).

How to choose the right chatbot for your team

Seeing these examples is one thing, but how do you pick the right one for your own business? It helps to ask a few key questions before you commit to a solution.

1. What's your primary goal? Are you trying to reduce support ticket volume, boost sales conversions, or just answer common employee questions? Different tools are built for different jobs. For instance, some platforms offer distinct "agent roles" for support teams and e-commerce stores.

2. How much setup are you willing to do? Do you have a team of developers ready to go, or do you need a no-code solution that works right out of the box? It's a good idea to look for platforms that let you start small, prove the value quickly, and then expand.

3. Where does your knowledge live? The best AI learns from the information you already have. Make sure any solution you consider can easily connect to your help desk, Confluence, Google Docs, and past conversations without forcing you into a painful data migration project.

4. How much control do you need? Can you easily define the bot's tone of voice and personality? Can you set clear, simple rules for when it should escalate a conversation to a human? You'll want to avoid "black box" solutions and look for platforms that give you plain-text control and rollout.

For a deeper dive into how businesses are using AI chatbots, the video below provides more real-world examples and strategies for improving lead generation and customer service.

This video provides more real-world examples and strategies for improving lead generation and customer service.

Moving toward AI teammates

The trend in chatbot development is moving from rigid bots toward more flexible AI teammates. AI can augment a team by handling repetitive tasks, allowing team members to focus on high-value conversations.

Some platforms are designed for quick setup, allowing an AI teammate to start contributing quickly.

Learn more about eesel AI