What is an Ecommerce Chatbot and Why It Matters (With Examples)

Types of Ecommerce chatbots

Let's quickly go over the different types of chatbots and how they work.

How do ecommerce chatbots drive sales?

Ecommerce chatbots don't just automate customer conversations. When set up thoughtfully, they can also help you sell more. How? By acting as your online shopper's virtual assistant — and supporting them exactly when they need it.

Here are some ways you can use chatbots to support customers from browse-to-buy and beyond — 

• Product recommendations: Use bots to analyse customer preferences and past purchases to suggest products they might like — and increase the likelihood of repeat purchases. 
• Abandoned cart recovery: Get your bots to remind shoppers about items left in their cart —and provide discounts or other incentives — to nudge them toward a purchase.
• Upselling and cross-selling: Program bots to suggest complementary products based on what customers are browsing (or buying) to increase the average order value.
• Personalized shopping guidance: Create “guide bots” to provide specialized guidance, such as picking a foundation color or jean style.
• Post-purchase engagement: Engage customers after their purchase with bot follow-ups and discounts to encourage repeat sales.
• Subscription management: Use chatbots to help customers easily adjust delivery schedules, pause their service, or renew a subscription — without navigating complex UI or contacting support.
• Visual search assistance: Enable shoppers to add a product photo to find similar-looking items available in your store. 
• Restock reminders: Set up bot flows to notify customers when it's time to reorder their favorite products — like groceries or consumer goods — ensuring they never run out. 
• Social purchasing: Allow shoppers to browse product catalogs and make purchases from within messenger apps and social platforms.
• Gift recommendations: Create personalized gift-finder bots to help shoppers pick the right gift by asking targeted questions about age, interests, and budget.
• Loyalty program management: Get your bots to encourage customers to join loyalty programs by prompting sign-ups after key actions like completing a purchase or leaving a review.

1. Hugg Beverages

Platform: WhatsApp 

Use case: Product recommendations and multilingual customer support

Hugg Beverages is an India-based D2C brand offering a range of herbal beverages formulated to address various health concerns, including digestive issues and insulin resistance. Their WhatsApp chatbot — built on Gallabox's no-code chatbot builder — allows them to automate basic customer inquiries and suggest beverages based on an individual's health concern. 

Hugg Beverages' WhatsApp Chatbot

As Harsh Doshi, the Founder of Hugg Beverages, tells Gallabox, “In today's world of instant gratification, the ability to answer customer queries quickly and accurately is not just an advantage, it's a necessity!”

Also read: How Gallabox's WhatsApp chatbots helped Hugg Beverages respond 800+ customer questions every day.

2. Sephora

Platform: Website 

Use case: Product recommendations

[Log into your Sephora account and go to profile > beauty preferences to try the chatbot.]

Sephora is a French multinational retailer specializing in personal care and beauty products. It was one of the first retail brands to implement a chatbot on their website — a reservation assistant and color match (shade finder) on Messenger. 

Sephora's Shade Finder Chatbot

Today, they have two hybrid chatbots on their website. The first is a detailed quiz that asks shoppers about their beauty preferences to recommend relevant products. The second is a “Shade Finder” that helps shoppers find their foundation shade based on their skin color and the foundation they're currently using. 

3. IKEA

Platform: Website 

Use case: Customer care

[Click the chat widget in the bottom-right corner of the IKEA website to talk to Billie.]

IKEA — one of the largest furniture retailers in the world — uses a custom bot named Billie to address customer inquiries on its website. According to the team, Billie is “best at helping you check your order status, giving you the opening hours of IKEA stores, rescheduling deliveries, and reporting missing or damaged items from your delivery.” 

IKEA's bot Billie suggesting sofas

You can also ask Billie for product suggestions — though it's a hit or miss most times, depending on the keyword you use. 

4. ASOS

Platform: Website and Facebook Messenger 

Use case: FAQs and AI Stylist (in beta)

[Head to ASOS's customer support page to check out the virtual assistant.]

ASOS is a British online fast-fashion and cosmetic retailer founded in London in 2000. Like many large retail outlets, they also use a customer service bot to address frequently asked customer care questions like order details and store policies. 

It doesn't give product suggestions or answer complex questions, but ASOS is also rolling out an AI Stylist Bot that's currently in beta.

The ASOS Virtual Assistant

Have you ever negotiated with AI? In 2024, ASOS was one of the first retailers to use an AI chatbot to allow shoppers to haggle for prices on its on-sale items. Though the chatbot is no longer active, some shoppers say they were able to get up to 40% off on items. 

5. Thread Bucket Studio

Platform: WhatsApp and WhatsApp chatbot embedded in website

Use case: Customer support

Thread Bucket Studio is an Indian ethnic wear brand for women. Being in India (WhatsApp's largest user base), they've used WhatsApp support to connect with customers where they already are. As a small team, they leveraged Gallabox's shared inbox and chatbots to handle customer support questions. 

The AI chatbot is for basic inquiries, and human agents are for the more complex ones. They say this approach has boosted team productivity by over 50%. 

Thread Bucket Studio’s WhatsApp Chatbot embedded in their website

Also read: How Thread Bucket Studio improved team productivity with Gallabox's WhatsApp chatbots

6. Casper 

Platform: Website

Use case: Product recommendations and customer support

[You can talk to Luna via the chat icon on their website.]

Casper offers a variety of sleep-related products, including mattresses, pillows, sheets, duvets, bed frames, and sleep accessories. Their chatbot, Luna, can guide shoppers through product selection, answer questions about returns/exchanges, and provide personalized recommendations.

Chatbot Luna's mattress recommendations for those with back pain

7. La Repa de Sueños

Platform: WhatsApp

Use case: Repair services

La Repa de Sueños is a Costa Rica-based, family-owned mattress company. They use a Spanish-language, rule-based chatbot, Julio, to handle repair requests on WhatsApp. Since they built it themselves, it's not the most sophisticated and doesn't support photos and videos. It simply collects mattress and repair details, helping the team manage inquiries with ease.

La Repa de Sueños' chatbot, Julio, asking questions in Spanish

Also read: How to build a powerful WhatsApp GPT bot

8. Sattvic Store

Platform: WhatsApp

Use case: Multilingual customer support and cross-selling

Sattvic Store is an online retail marketplace selling locally sourced, organic health supplements, herbs, extracts, and more. They implemented a multilingual — English and Hindi — WhatsApp chatbot using Gallabox to address frequently asked customer questions. Two other ways they use WhatsApp chatbots are to:

• Cross-sell relevant products to past customers by segmenting contact lists based on purchases.
• Collect customer details and sync them with their CRM for lead generation.

How Sattvic Store uses WhatsApp chatbots (and automation)

Also read: How Sattvic Store reduced RTO by 50% with Gallabox's no-code WhatsApp chatbots

9. H&M

Platform: Website

Use case: Customer care and checking product availability

[You can access the chatbot via the chat icon on their website.]

H&M is a Swedish multinational fashion retailer. They use a rule-based chatbot on their website to help with customer support inquiries. One thing to take inspiration from H&M is their “Check availability” feature, where you can upload an image of a product to see if it's available or when it would be restocked. They also allow you to download a transcript of your conversation. 

H&M's chatbot

10. Macy's 

Platform: Website

Use case: Customer support

[You can access the chatbot by going to Your Account > Contact us.]

Macy's is one of America's oldest department store chains that also has an online store. And they also have a chatbot to answer basic questions. There are two ways Macy's approaches chatbots differently — first, they collect your contact details before allowing you to talk to the bot.

Macy's chatbot on how it can help

And anytime the bot stumbles, it automatically connects you with a human agent — skipping the process of frustrating back-and-forth responses like, "Can you repeat that?"

Better Customer Support

Customers expect immediate answers, while brands need cost-effective ways to improve satisfaction. Ecommerce chatbots deliver both.

• 24/7 availability: Unlike human agents, chatbots operate around the clock to assist customers at any time — be it Sundays, holidays, or sick days.
• Instant answers: Chatbots handle repetitive questions (e.g., shipping times, return policies) so human agents can focus on complex cases.
• Multilingual bots: By deploying chatbots in multiple languages, brands can engage regional shoppers and expand their customer base.

Personalized shopping experience

Ecommerce chatbots — especially the AI-powered ones — are a great (and super simple) way to personalize a shopper's purchasing journey — from product discovery to post-purchase recommendations. Here's how:

• Real-time recommendations: By acting as virtual personal shoppers, chatbots can offer real-time product recommendations based on user behavior. For example, if a customer is looking at winter boots, the chatbot might suggest complementary items like socks or waterproof sprays.
• Just-for-you discounts: Chatbots can send tailored discounts and promotions based on a customer's shopping behavior. For example, a first-time buyer can get a discount code when starting a chat, encouraging them to complete their purchase.
• Behavioral targeting: Chatbots can use behavioral targeting techniques to deliver personalized messages based on user activity on the website or app. If a customer frequently browses but does not purchase, the chatbot can pop up with a discount to get them to make a purchase.

1. Define clear use cases

Before setting up your chatbot, determine what problems it should solve — customer support, product recommendations, or something more niche like finding a foundation or suggesting complementary purchases? This way, your chatbot supports your business goals and is actually useful to your customer base.

Without clear use cases, you risk low customer adoption and eventual shutdown — like eBay's ShopBot.

Pro tip: Start with a few core functions and add more as you learn from customer interactions.

2. Choose the right chatbot type

The type of chatbot you choose depends on your customer needs and the complexity of interactions you want to automate. Some questions to ask yourself are:

1. Do your customer interactions primarily involve answering frequently asked questions (FAQs) or providing basic information?
2. Are the majority of your customer inquiries predictable and follow a set pattern?
3. Are you comfortable with manually updating and maintaining the chatbot's responses?
4. Do you anticipate a low volume of complex or nuanced customer inquiries?
5. Do you prefer a chatbot that offers a controlled and structured conversation flow?

If you answer “yes” to most questions, then you'd do well with a simple, rule-based chatbot. And if most of your answers are “no,” then we suggest going with an AI-powered one. Not clear about your goals? Then, pick a hybrid chatbot so that you can update it as you scale.

3. Prioritize user experience (UX)

A great chatbot is all about the “experience”. Good UX ensures that the chatbot feels natural, easy to use, and supportive of the shopping journey — instead of taking away from it. Some UX factors to focus on are:

• One-handed mobile use: Since most shoppers interact with chatbots on their phones, ensure that buttons are large enough to tap easily and that the chatbot window doesn't cover the entire screen.
• Human-like replies: Aim for conversational replies. Draft pre-defined replies (or pick an AI bot) that are friendly and helpful — like a real person.
• Clear navigation flows: Design easy-to-follow paths so shoppers can quickly find what they want. 
• Quick reply options: Don't make shoppers type out everything. Provide buttons for FAQs like "Track My Order," "View Discounts," or "Chat with Support."

4. Train your chatbot with real customer conversations 

This one's for the AI chatbots, as they're only as good as the data they learn from. Feed your chatbot real customer conversations, FAQs, and past support interactions. That way, the chatbot understands intent, picks up on context, and delivers human-like replies that actually help.

Also, make sure to update your privacy policy to inform customers that their conversations will be used for AI training and let them know if this data will be shared with any third-party AI tools. 

Levi's does this quite well by sharing a link to the privacy policy right at the beginning of the conversation. 

5. Integrate with existing systems

A chatbot on its own is helpful, but a chatbot that connects to the rest of your tech stack is even better. We suggest integrating with the following platforms:

• CRMs to pull up customer history, preferences, and past purchases
• Inventory systems for real-time product availability checking
• Payment gateways so customers can make payments directly from the chatbot
• Logistics partners to provide instant updates on order status, shipping information, and estimated delivery times
• Marketing automation platforms to send targeted promotions and offers based on customer behavior 

Challenge 1: Chatbot responses feel too robotic

A stiff, scripted chatbot can frustrate customers if conversations are long. More so, if it's an AI bot that doesn't gauge context or tone correctly. 

What you can do:

• For rule-based chatbots: Write conversational replies and expand your decision tree to include more response variations to address nuance.
• For AI chatbots: Pick a chatbot solution that accurately understands the context, intent, and sentiment behind customer messages. 

Challenge 2: Chatbot lacks personalization

A generic chatbot with the same responses can lead to a potential loss in sales, especially if you're using it for things like abandoned cart recovery, upselling, or personalized recommendations and offers. 

What you can do:

• For rule-based chatbots: Set up predefined customer segments (e.g., new visitors, repeat buyers, VIP customers) and deliver responses accordingly. If it's a new customer, you can also offer product recommendations based on simple multiple-choice questions.
• For AI chatbots: Integrate the chatbot with your CRM to understand past purchase history and website tracking for real-time personalization.

Challenge 3: Customers want a human agent

Some problems are too complex for a chatbot, and customers may get frustrated if there's no option to talk to a human.

What you can do:

• For rule-based chatbots: Add a “Talk to an Agent” button for easy human escalation.
• For AI chatbots: Set handoff rules where the bot detects complex issues and automatically routes to the right human agent.

Challenge 4: Maintaining and updating the chatbot

A chatbot is not a "set it and forget it" tool. Without consistent updates, it quickly becomes outdated — resulting in irrelevant responses and a frustrating customer experience. 

What you can do:

• For rule-based chatbots: Review chatbot logs monthly to see where users get stuck to update your scripts, and add new FAQs and guides based on customer trends and feedback.
• For AI chatbots: Pick a chatbot platform that periodically retrains its AI model with updated data sets to ensure it stays current with evolving language patterns and social trends.

1. What are the limitations of current AI chatbots in ecommerce?

Despite technological advances, AI chatbots aren't humans. They have a limited understanding of intent and sentiment, lack human empathy, and can be repetitive. 

2. How do customers perceive AI chatbots in ecommerce?

Customers appreciate AI chatbots for 24/7 support and instant replies, which they say make shopping easier. At the same time, they do get frustrated when bots give irrelevant answers, don’t understand context, or have a confusing interface.