Conversational AI for product discovery, order support, returns, and personalised recommendations, trained on your catalogue and business specifics. Built for retailers and eCommerce brands that need more than a basic FAQ bot.
Keyword search fails when customers describe what they want in natural language. They leave frustrated without discovering products that match their intent.
Where's my order? How do I return this? Every purchase generates follow-up questions that overwhelm your support team during peak seasons.
Decision-tree bots that can't understand context or preferences drive customers to competitors who provide better digital experiences.
Your recommendation engine works in newsletters but goes silent when customers are actively shopping and asking questions on your site.
Understands natural language descriptions and browsing context to surface the right products. "I need a gift for my dad who likes hiking" becomes actionable.
Real-time order status, shipping updates, and delivery estimates pulled directly from your fulfilment system.
Guided returns flow with policy-aware responses. Initiates RMAs, suggests exchanges, and reduces return friction.
Uses your product specs, size charts, and fit details to give shoppers confident sizing advice and reduce size-related returns.
Re-engages abandoned sessions with contextual nudges, answers last-minute objections, and suggests complementary products.
Same AI across your website, mobile app, WhatsApp, and social channels. Consistent experience everywhere your customers shop.
Yes. ChatBotHouse integrates with your eCommerce platform (Shopify, WooCommerce, Magento, custom) via API. The AI accesses live product data, pricing, inventory levels, and order status.
In our experience, customers who engage with AI product recommendations tend to convert at higher rates. The AI helps reduce abandoned carts by answering purchase-blocking questions before customers leave.
Yes. The AI walks customers through your return policy, initiates return requests, provides shipping labels, and processes exchanges, all within the chat conversation. It does this by integrating with your current systems.
Rule-based bots follow scripted decision trees: "Click here for returns, click here for sizing." They break the moment a customer asks something that isn't in the script. A custom AI shopping assistant understands natural language and context. A customer who says "I need a waterproof jacket for hiking in Scotland in November, budget around £150" gets actual product matches from your catalogue. The AI can ask follow-up questions, compare options, and guide the customer all the way through to purchase, just like your best in-store staff would.
Size-related returns are one of the biggest cost centres for online fashion retailers. An AI chatbot trained on your product specs, size charts, and fit details can give shoppers confident sizing advice before they buy. "I usually wear a medium in Zara, what size should I get?" becomes a real conversation where the AI factors in your specific brand's fit. The result is fewer bracket orders and fewer "wrong size" returns. Several fashion retailers have seen measurable reductions in size-related returns after deploying conversational sizing guidance.
Post-purchase questions are the highest-volume category for most online retailers: "Where's my order?", "How do I return this?", "When will my refund arrive?" An AI chatbot connected to your order management and fulfilment systems gives customers real answers, not canned responses. It pulls live tracking data, walks customers through return steps, and checks refund status in real time. During peak seasons like Black Friday or holiday sales, the chatbot handles the surge without hiring seasonal staff. Your support team focuses on the complex cases: damaged items, billing disputes, and situations that need a human judgment call.
Yes, and this is where AI really outperforms traditional product filters. A shopper can say "compare these two coffee machines, I care most about ease of cleaning" and the AI pulls specs, reviews key differences, and highlights what matters based on the shopper's stated priorities. It works across your full catalogue because it understands product attributes and descriptions, not just category tags. For retailers with thousands of SKUs, this turns browsing fatigue into a focused, helpful conversation.
We'll build a working demo using your actual products and content. See conversational commerce in action before committing.
No commitment. No sales deck. Just a real conversation about your use case.