AI Chatbot for E-commerce

Natural language product discovery: a customer types "waterproof hiking boots under $150 in size 10" and the chatbot returns a filtered, ranked set of matching products with images, prices, and an add-to-cart button -- all without leaving the chat window. Conversational filtering and sorting: "show me only the ones in black" or "sort by best reviews" work as follow-up messages. Side-by-side product comparison on request. The assistant can initiate checkout, apply discount codes, and surface current promotions. Works on web and mobile, and can be embedded in any page on your storefront without requiring a new platform.

A customer types their order number or the email address they ordered with -- the bot retrieves live status from your OMS or directly from the Shopify Orders API and responds with the current status, carrier, tracking number, and estimated delivery date. Proactive outbound messages for key shipping events: order confirmed, dispatched, out for delivery, delivered. Delivery exception handling: if a parcel is delayed or shows a failed delivery attempt, the bot notifies the customer and offers options. Re-delivery scheduling integrated with your carrier API where supported. The bot that handles tracking queries at 2am without a support agent.

A customer initiates a return through the chatbot. The bot checks return eligibility against your policy rules -- purchase date, product category, return window, condition requirements -- and tells the customer immediately whether the item qualifies. If it does, the bot generates a return shipping label, sends it to the customer's email, and creates the return record in your OMS. It handles the main edge cases: damaged items received, wrong item delivered, change of mind returns with restocking fees. Refund or exchange trigger is sent to your OMS automatically on return receipt confirmation. Reduces returns handling time and removes the back-and-forth from the process entirely.

The bot answers product-specific questions from your catalogue and spec sheets: "is this pan dishwasher safe?", "does this jacket come in XL?", "what is the weight limit on this chair?" It pulls answers from structured product data and, where specs are in documents or PDFs, from a parsed knowledge base. It also answers shipping, payment, and policy FAQs -- delivery timeframes by region, payment methods accepted, gift wrapping availability -- from a knowledge base built from your existing help centre content. When confidence is low or the query falls outside the knowledge base, the bot acknowledges the gap and escalates to a human agent rather than generating a wrong answer.

Review request sent at the right moment after delivery -- not immediately on dispatch, but after the customer has had time to use the product. Reorder prompt for consumable products -- the bot tracks purchase date and sends a reorder reminder at the predicted replenishment point for products like supplements, coffee, or skincare. A check-in message for higher-value purchases: "how are you getting on with your new espresso machine?" with a link to setup guides. Loyalty points balance and tier progress queries handled in chat. These flows run on triggers rather than a fixed schedule, so the timing is based on actual delivery and usage signals rather than generic timers.

The bot handles routine queries automatically. When a customer is frustrated (detected via sentiment signals in message content), the query is outside the bot's knowledge, or the bot's confidence score falls below a defined threshold, the conversation is transferred to a human agent. The full conversation history is passed to the agent so they can read the entire exchange before responding -- no customer has to repeat themselves. We build integrations with Gorgias, Zendesk, Freshdesk, and Intercom so the handoff lands in whatever queue your team already works from. Handoff rules are configurable: you decide which query types always go to a human and which the bot is trusted to handle independently.