What is an AI shopping assistant?

What it does

• Understands natural requests. A shopper can write “a gift for my wife under $50” instead of guessing keywords.
• Asks follow-up questions to narrow down the options, like a salesperson would.
• Recommends products from the current catalog, with prices and availability.
• Answers questions about products, delivery, returns and payment.
• Takes actions, such as adding products to the cart or checking an order.

How it works

1. It connects to the store’s data: products, variants, prices, stock, policies and FAQs.
2. The shopper asks a question. A language model works out what they want.
3. It looks up the facts, such as searching the catalog or retrieving a policy.
4. It writes a reply based on what it found, often with product cards.

Answering from retrieved store data, not from memory, helps reduce made-up answers. It doesn’t remove them completely, so a good tool lets you review conversations.

AI shopping assistant vs chatbot vs helpdesk

Swipe to see the full table.

Which stores benefit?

• Stores where shoppers ask questions before buying, such as about compatibility, sizing or ingredients
• Larger or more technical catalogs that are hard to browse
• Stores selling in several languages or markets
• Teams answering the same questions again and again

A store with a few simple products and few questions may not need one yet.

What to watch out for

• Wrong answers. Test with real questions, and review conversations regularly.
• Usage limits and billing. Check what counts as usage and what happens when you go over. See what they cost.
• Privacy. Check where data goes, and ask for a data processing agreement. See how Talkom handles data.
• Measuring results. Look for attributed orders and revenue, not only chat counts.

An example: Talkom

Talkom is one AI shopping assistant. In its customer data, 36% of conversations ended with an add-to-cart, and 15% with an order. For other options, see our comparison.

Frequently asked questions