AI chatbot

AI Chatbot for Upselling and Cross-Selling

Suggestions that answer the question, not a bot that pushes the expensive one

Upselling in chat only works when the suggestion is a better answer to the question the shopper asked. Vatdi suggests products from your own catalogue with image, price and link, can rank by units actually sold rather than by guesswork, and offers a coupon when its real conditions are met. You control how many products appear and whether the AI leads with them at all.

Last updated September 15, 2026

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95+ languages
Human handover included

Vatdi Assistant

The gap without an assistant

Missed upsell opportunities during support chats
Static recommendation widgets have low click rates
Sales team cannot upsell after hours
Pushy upselling annoys customers

How Vatdi closes it

What the assistant does for you

Cart-based accessory recommendations
Plan upgrade suggestions
Bundle deal promotion
Post-purchase add-on offers

The difference between a suggestion and a push

A shopper asking "will this fit a 15-inch laptop" wants a yes or a no, and then the sleeve that does fit. That is an upsell nobody resents. A bot that answers with the most expensive item in the category has simply moved the sales pressure into the chat window, and shoppers close it.

The practical rule: suggest when the suggestion is the answer, and cap how many products appear. Vatdi lets you set that limit, control whether product links are included at all, and set the tone and reply length so the AI does not turn every answer into a pitch.

Best sellers, from real sales

Most widgets that claim best-seller recommendations are re-ranking whatever the catalogue feed gave them. Vatdi's native plugins send the number of units actually sold, and the AI sorts by that when a shopper asks what is popular. If a store has not sent sales data, the AI does not call anything a best seller. That constraint is the point: a fabricated "our most popular" is the fastest way to lose a customer's trust in every other answer.

Sales counts come from the OpenCart 3 and 4, WooCommerce, Shopware and Magento plugins today.

Coupons that respect their own rules

You create coupons with conditions; the AI offers an active one when the conversation matches. It cannot invent a code, cannot stack discounts you did not configure, and does not offer one to every visitor by default. That keeps the discount as a closing tool rather than a margin leak.

Cross-selling after the sale

The strongest cross-sell moment is a customer already in a conversation about an order they have placed. With order lookup on WooCommerce, OpenCart 3 and 4, PrestaShop, Magento, Shopware, Joomla (VirtueMart and HikaShop) and Drupal Commerce, the AI can confirm what shipped and answer a "what else goes with this" question against the same catalogue, with your accessory products alongside.

Three moments where a suggestion lands

Compatibility questions. "Does this fit my model" is a buying signal with a specific answer. The reply is yes or no plus the item that does fit — the highest-converting suggestion there is, because it was requested.

Out of stock or discontinued. A dead end becomes a choice: two or three near alternatives from your catalogue, with prices, rather than an apology and a closed tab.

"What do you recommend." An open question deserves a grounded answer. Ranking by units actually sold makes the reply defensible, and it is the one case where leading with best sellers is genuinely helpful rather than lazy.

The moments that do not work are just as consistent: attaching an accessory to a complaint, upselling before the original question is answered, and suggesting a more expensive item when the shopper stated a budget. Tone and reply-length settings exist so the AI stays out of those.

Where product data lets suggestions down

Weak suggestions are almost always a data problem rather than a model problem, and the causes repeat across stores.

Descriptions written for the category page. Two lines of marketing copy give the AI nothing to match a specific question against. One paragraph of plain facts per product fixes it.
Attributes trapped in images. Dimensions, compatibility and materials inside a graphic are invisible. Put them in text and those questions become answerable.
Internal naming. Customers do not search your SKU vocabulary. Adding the everyday phrasing to the description closes most of the gap.
No accessory relationships written anywhere. If nothing on the site says which case fits which model, no retrieval system can invent it.

The insights report is the shortcut: it lists what people actually asked, and the unanswered questions are a ready-made list of the product copy worth fixing first.

What it costs to run this at volume

Suggestion-heavy stores tend to have long conversations, which is exactly where per-message and per-resolution pricing gets expensive. Vatdi meters conversations, not messages: a chat that runs twenty turns costs the same as one that runs three. The free plan covers 15 conversations a month, Starter is $4.49 for 150, and Grow is $7.49 for unlimited conversations with unlimited knowledge items. No plan charges per seat, so putting the whole team on the inbox is free.

Measuring whether it works

Every conversation is graded 0 to 10 with advice on what to fix, and reports cover conversations, leads, ratings and missed handoffs. The insights report lists what people actually ask, which is where the next set of accessory pages usually comes from. Advanced analytics adds resolution rate, unanswered questions and page-level activation.

One habit is worth more than any setting: read the ten most recent conversations where a product was suggested and ask whether the suggestion answered the question. If it did not, the fix is usually in the product description rather than in the bot.

Where it runs

Native plugin on your platform, widget on everything else

Install on your store in one click, or paste the one-line widget on any other site.

WordPress

OpenCart

Shopify

PrestaShop

Magento

Shopware

Joomla

Drupal

Frequently Asked Questions

How does the AI decide what to suggest?

It retrieves from your own catalogue against the question asked, and can sort by units actually sold when the shopper asks what is popular. You set how many products a reply may contain.

Can it push a discount to close a sale?

It can offer coupons you have created, when the conversation meets their conditions. It never invents a code or discounts by default.

Does it work on any platform?

Product suggestions work anywhere the catalogue is synced or crawled. Real sales-count ranking needs the OpenCart, WooCommerce, Shopware or Magento plugin.

Will it turn every answer into a sales pitch?

Only if you configure it that way. Tone, reply length, emoji use and whether product links appear at all are settings.

What does it cost?

Free for 15 conversations a month with every feature on, $4.49 a month for 150, $7.49 for unlimited conversations. No per-seat or per-resolution fees.

Try it on your own store

The free plan holds 15 conversations a month with every feature switched on. No card, no trial clock.

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