06/10/2026
A relevant product recommendation can still be a weak shopping answer. If a chatbot shows only the item name, the customer has to leave the conversation to check the image, discount, available options, and final offer.
That gap is easy to miss because the reply may look correct at first. The product matches the request, the category is right, and the budget seems close. But in a real store journey, people do not decide from a title alone.
A product card gives them the signals they need before they click: what the item looks like, whether there is a special offer, how the cost changes across variants, and whether the visible range matches what they expected. When chat removes those signals, it can make the buying path feel faster at first but less useful in practice.
This is especially important for configurable, grouped, and bundle products. A clean number in a chat reply may hide a cheaper variant, a “from/to” range, or a crossed-out regular amount next to the sale offer. The item can be relevant, while the commercial context still feels incomplete.
A better store assistant keeps enough buying context inside the conversation. It should help the customer understand the option clearly enough to decide whether to open it, compare it with another item, or move closer to purchase.
In our eChat extension for Magento 2, the chatbot can show product images, sale prices, price ranges, and strikethrough regular prices where relevant, so recommendations feel closer to the catalog experience customers already understand instead of a plain text suggestion.
Learn more: https://mirasvit.com/magento-2-gpt-chatbot.html
