AI Chatbot for E-commerce

It is an automated answering system that learns from your own product catalogue, prices, shipping and returns policies. Customers type the way they normally would, and it understands and answers from real data rather than offering a generic greeting.

Unlike fixed button flows, an AI chatbot follows the thread of a conversation: when a customer follows up about the product just mentioned, it still knows which model is meant and does not make them type the name again.

1Advising on products by need

The customer describes a general need; the chatbot asks about budget and intended use, then suggests a few options instead of leaving them to filter the whole catalogue.

2Checking order status

The customer enters an order code or phone number and the chatbot returns whether it is being packed, out for delivery or delivered, which cuts the repeated messages about the same order.

3Answering on shipping cost and time

Delivery charges by area, the expected time, the conditions for free shipping — questions that come up right before checkout.

4Explaining returns and warranty

Return conditions, deadlines, what paperwork to keep: the chatbot sets it out exactly as your published policy states, so nobody misunderstands and complains later.

5Capturing potential customers

For an item temporarily out of stock, or a customer still deciding, the chatbot asks for contact details so the sales team can follow up rather than losing the interest entirely.

1The customer asks about a product

A question about colour, size or material starts it, usually right on the product page.

2The chatbot clarifies the need

It asks for a few more details to understand what they want, instead of answering vaguely and leaving them to weigh it up.

3It gives the deciding information

Price, availability, shipping cost and delivery time — together these are usually what a customer needs before placing the order.

4It moves them to purchase or to a person

If they are ready to buy, the chatbot takes them straight to ordering; anything needing special handling goes to a member of staff with the conversation attached.

Most messages arriving at an online shop circle a few topics: where is my order, is it in stock, how do returns work. The chatbot clears that group so staff can concentrate on complaints and situations that need judgement.

One point worth noting: message volume jumps during a promotion, exactly when the team is busiest. The chatbot handles unlimited conversations in parallel, so customers are not queueing for their turn.

1Product catalogue and stock

Names, descriptions, variants, prices and availability. This is the most important layer, and in e-commerce also the fastest changing.

2Shipping and payment policies

Charges by area, delivery times, accepted payment methods, and the conditions for free shipping.

3Returns and warranty policies

Deadlines, conditions, how the process runs. Without this the chatbot answers incompletely and customers misread their entitlements.

4Updating for promotions

Prices and offers change with each campaign. The chatbot's data has to be synchronised when a campaign starts and when it ends.

1Never confirm stock it cannot see

If stock is not synchronised in real time, the chatbot should say the availability needs confirming rather than assert it and have to tell the customer afterwards that it has sold out.

2Spell out promotion conditions

Which products a discount code applies to, until when, whether it stacks. This is the EEAT principle the NAVI team stresses with e-commerce clients: state the conditions while advising, not leave the customer to discover them at checkout.

3Never decide on refunds

For a return or refund request, the chatbot records the details in full and passes them on. It does not commit to an outcome on behalf of the team responsible.

1Answers from your own data

NAVI's AI chatbot learns directly from the product catalogue, price list and policies you provide, not from generic information.

2Capturing requirements and contact details

The product of interest and the customer's phone number are recorded in the conversation and passed straight to the sales team.

3Conversations on the dashboard

Everything advised is stored, so the business can see which products are asked about most and where customers get stuck before buying.

4Putting it on the website

One line of script and the chatbot is live, with no technical team needed to reach into the existing sales system.

Own-brand webstores, marketplace shops that also sell through a page, brands spanning several categories — all can use an AI chatbot, as long as customers message before they buy. The larger the catalogue and the more variants, the more lookup time it saves for customers and staff alike.

1Can it look up orders?

Yes, where order data is connected to the system. The customer enters an order code or phone number and gets the current status.

2Can it recommend products by need?

Yes. It asks about budget and intended use, then suggests a few suitable options instead of listing the whole catalogue.

3Does it handle refund requests itself?

No. It records the request and explains the process; the final decision rests with the team responsible.

4How long does a rollout take?

With the product catalogue and policies prepared, integration usually takes only a few days.

5Does it work outside office hours?

Yes, and that is where it shows its value most, since most online shopping happens in the evening when the team has finished.

An AI chatbot for e-commerce holds onto customers while they are still deciding, instead of letting one unanswered question cost the order. If you also need after-sales care, see the AI chatbot for customer service, running alongside to bring customers back next time. Read more about the solution at NAVI Website.