4 Conversational Commerce Examples & How They Boost Sales

Online shoppers face a fundamental problem: browsing alone through endless product pages rarely matches the experience of talking with a knowledgeable sales associate. Conversational commerce changes this by enabling real-time chat or voice interactions where customers ask questions, receive tailored recommendations, and complete purchases without leaving the conversation.

In this blog, we'll examine where conversational commerce fits in the customer journey, which technologies power it, what measurable benefits it delivers for eCommerce brands, and how leading companies implement it successfully.

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What Is Conversational Commerce?

Conversational commerce is the interaction between shoppers and brands through real-time chat or voice, where a digital assistant or human agent helps users discover, select, and purchase products in the same conversation. It transforms online shopping from a one-sided browsing experience into a two-way dialogue that feels intuitive and personal.

Instead of searching through endless pages, you can ask questions, get tailored suggestions, and check out without leaving the chat. This shift merges personalization and convenience, creating a guided journey rather than a self-service process.

» Find out why conversational commerce is so popular

Where Conversational Commerce Fits in the Customer Journey

• Product discovery: At this stage, conversational tools help users explore products through personalized recommendations and contextual questions. Instead of searching manually, shoppers receive relevant suggestions based on their needs and preferences.
• Purchase: During purchase, the conversation becomes transactional. The system confirms availability, processes payments, and finalizes the order within the same thread — reducing friction and abandoned carts.
• Post-purchase: After checkout, conversational systems assist with delivery tracking, returns, and follow-up questions. This continued engagement helps strengthen trust and encourages repeat purchases.

» Read more: How to reduce cart abandonment rates

Measurable Benefits for eCommerce Brands

• Companies using chatbots report faster support times, with up to 4 minutes saved per query, which improves customer satisfaction.
• Conversational engagement drives higher conversion rates, as AI-assisted shoppers convert at 12.3%, compared to 3.1% without chat.
• Businesses report an average 67% increase in sales after implementing conversational tools.
• Real-time conversation helps overcome the 70% average cart abandonment rate by maintaining context until checkout.
• Around 90% of customers say that responsive support makes them buy from a brand again, showing strong gains in loyalty.

» Here are more benefits of using AI in eCommerce personalization

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Traditional Online Shopping vs. Conversational Commerce

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Technologies Powering Conversational Commerce

Modern conversational commerce relies on three connected technology layers working together seamlessly:

• AI chatbots and voice assistants: These tools interpret natural language, recommend products, and complete orders inside the chat.
• Messaging platforms: Platforms such as WhatsApp and Facebook Messenger host these conversations, allowing shoppers to communicate with brands in familiar, real-time environments. Studies show that using WhatsApp Business can increase sales by about 27% due to faster response times and smoother engagement.
• Back-end integration: Product databases, payment gateways, and support systems are synchronized so that every interaction — from inquiry to delivery — happens within one continuous experience.

» Find out why chat AI is the next step in eCommerce

4 Real-World Conversational Commerce Examples

1. Fashion: Zalando’s AI Assistant

Zalando redefined digital styling with its ChatGPT-powered AI Fashion Assistant, rolled out across all 25 European markets in 2025. This tool allows shoppers to ask natural questions like “What should I wear for a wedding in Santorini?” and get intelligent outfit suggestions instantly.

The upgrade from GPT-3.5 to GPT-4o mini improved contextual understanding, resulting in a 23% increase in product clicks and 41% more wishlist additions.

The assistant focuses on contextual understanding and multilingual support, interpreting real-world intent instead of keywords. This eliminated friction between browsing and buying.



Best practice takeaway: Focus on human-like, conversational discovery rather than transactional keyword search. Contextual AI recommendations create trust and engagement at scale.

2. Beauty: L’Oréal Paris – Beauty Genius

L’Oréal Paris introduced Beauty Genius, a generative AI and AR-powered beauty advisor. It combines decades of L’Oréal’s expertise with dermatologist insights and data from over 750 products to offer custom routines. The AR try-on feature, trained on 6,000 inclusive images and tested with 10,000 products across 50 countries, lets users visualize looks in real time.

Beauty Genius merges AI context awareness with hyper-personalized virtual try-ons, allowing users to privately discuss and experiment with beauty concerns.



Best practice takeaway: Blend visual interactivity with conversational guidance. When customers can see results instantly and ask follow-up questions, confidence and conversion rise dramatically.

» Here are 6 modern strategies to increase conversion rates

3. Food: Wendy’s – FreshAI Drive-Thru Ordering

Wendy’s developed FreshAI with Google Cloud to automate drive-thru ordering at more than 160 locations (expanding to 600 by late 2025). The system understands conversational phrasing — interpreting “large chocolate milkshake” as a “large Frosty” and suggests relevant add-ons. Results show an 86% accuracy rate and 22-second faster order times, along with higher average checks.

By blending natural language understanding with upselling logic, Wendy’s created a fluid, human-like experience that improves order speed and basket size.



Best practice takeaway: Combine AI-driven personalization with operational efficiency — success lies in enhancing, not replacing, the human touch in service.

» Need more help? Here's how to add natural language search to your eCommerce store

4. Technology: Lenovo – Premier Support AI Chatbot

Lenovo’s Premier Support AI Chatbot transformed customer care by using generative AI to manage multilingual technical support across global centers. Customers describe problems naturally, and the AI gathers diagnostic data before connecting them to agents. Results show a 20% drop in average handle time and a 15% boost in agent productivity.

The system’s context-aware intake removed repetition and frustration from tech support, improving resolution speed and satisfaction.



Best practice takeaway: Use conversational AI as a triage layer — it empowers human agents to focus on solutions, not data collection.

» Read more: How to create a personalized brand experience to drive CLV

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Common Mistakes and Solutions in Conversational Commerce

Mistake 1: Treating Conversational Commerce as “Set and Forget”

• Explanation: Many brands assume chatbots and AI assistants will perform without ongoing updates or oversight. This can backfire: a 2024 Gartner survey found 64% of customers prefer not to interact with AI for service, and 53% would consider switching brands if they realized AI replaced a human.
• Solution: Continuously monitor and refine your conversational tools. Regularly update scripts, AI training data, and responses based on real interactions. Blend human support where needed to maintain trust, ensure smooth experiences, and protect your brand reputation.

» Here's how to improve the customer experience with AI

Mistake 2: Over-Relying on Bots Instead of Human Support

• Explanation: While chatbots can handle repetitive questions, over-dependence risks alienating users. Over half of customers still prefer human interactions, while only 12% favor bots. Ignoring this can reduce engagement and damage loyalty.
• Solution: Use AI to augment, not replace, humans. Route complex inquiries to live agents, and maintain a seamless handoff within the same conversation. This keeps the experience efficient, personalized, and trustworthy.

Mistake 3: Ignoring Evolving Channels

• Explanation: Brands sometimes invest in emerging technologies like voice commerce or AI search before the ecosystem is ready, leading to low ROI.
• Solution: Focus first on proven channels such as WhatsApp and Facebook Messenger, which already drive measurable revenue. Pilot newer channels like voice or AI search cautiously while monitoring adoption and conversion trends.

» Learn how to implement AI in your eCommerce store

Moving Forward With Conversational Commerce

Conversational commerce succeeds when brands combine AI efficiency with human judgment, meeting customers where they already communicate. The most effective implementations focus on proven channels like WhatsApp and Facebook Messenger before experimenting with emerging technologies, ensuring every interaction adds value rather than frustration.

Fast Simon's AI personalization helps eCommerce merchants implement conversational experiences that understand shopper intent, recommend relevant products in real-time, and guide customers from discovery through checkout within a single thread.

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