The right add-on, at the right moment:
never a generic pitch
Most upsell prompts are the same banner for every customer, so most customers ignore them. An agent reads what a customer is actually asking about or buying. It suggests one relevant add-on at the moment it fits, instead of a generic pitch nobody asked for.
Why most upsell prompts get ignored
Most online stores run one upsell mechanism for every customer: a banner, a pop-up, a fixed “customers also bought” row. It shows the same way no matter what the person is actually looking at. Teams that test this usually find a large share of customers simply tune it out, because the suggestion was never built around their specific order.
Timing is the second problem. A relevant add-on can land at the wrong moment: before a customer has decided on the main item, or after checkout when the cart is already closed. Either way it reads as noise rather than help. The same suggestion, placed right after a customer confirms the item they actually want, lands completely differently.
Overreach is the third cost. A team that notices upselling works sometimes pushes too hard, suggesting an add-on in every message. That trains customers to ignore the business’s messages in general, not just the upsell ones. The signal gets lost because there was never a limit on how often it fires.
What the agent reads, suggests and tracks
The agent reads what a customer is asking about or has already put in the cart. It checks that against bundle and relevance rules your team built from the actual catalogue. Then it suggests one specific add-on at the moment it fits, usually right after the customer confirms their main choice in chat or at checkout. The suggestion names the actual product and the actual reason it pairs with what they are buying, not a generic “you might also like” line.
If the customer declines or ignores the suggestion, the agent does not repeat it in the same conversation. One relevant offer, clearly stated, is the rule, not a sequence of nudges. For stores that sell through chat as well as a storefront, the same logic runs in Telegram, WhatsApp or web chat. A customer asking a support question about one product can still get a relevant suggestion, without it feeling like a sales interruption to their actual question.
Post-purchase, the agent can send one follow-up a few days later for consumables or recurring items: a refill, a companion product. It is timed to when the customer would plausibly be ready for it, not immediately after the first order lands. Every suggestion made, and whether it was accepted, is written to your CRM. Your team sees which combinations actually convert, and retires the ones that do not.
What stays with humans
The bundle and relevance rules are built and approved by your team, not guessed by the agent. Any pricing change, discount, or custom bundle outside the approved list goes to a person. The agent suggests. It does not negotiate price or create a one-off deal on its own.
Guards
The agent introduces itself as an AI assistant at the start of every conversation. Every suggestion is logged against the rule that triggered it and whether the customer accepted it, so your team can audit what is actually working. New bundle rules go through a review step before going live. A frequency cap keeps the agent from suggesting more than once per conversation, no matter how the rules are written. A kill switch turns suggestions off instantly if something looks off in the data.
Price and timeline
| Option | Price | What it covers | Timeline |
|---|---|---|---|
| Single automation | from $600 | One channel, fixed bundle rules, CRM logging | 4 to 8 days |
| Department package | from $2,500 | Upsell and cross-sell plus win-back and abandoned cart recovery | 2 to 4 weeks |
Running cost is usually $20 to $70 a month in model usage, depending on conversation volume.
Related
Pair this with abandoned cart recovery to catch the customers who did not finish checking out at all. Win-back of inactive customers fits once a customer has gone quiet for longer than a single cart. See the full package breakdown on the AI agents service page. For how targeted selling moved real revenue, see the Balkans supplements store case study, where average order value rose after the funnel was rebuilt. The sports nutrition relaunch case study covers a related rebuild.
Want relevant add-ons suggested automatically, without the pitch fatigue? Get in touch and we will look at your catalogue for the obvious pairings first.
Tired of doing this by hand? We can take the whole routine off your team, not only this step: Routine takeover, from $400 →
FAQ
How much does upsell and cross-sell automation cost?
From $600 for one channel with a fixed set of bundle rules, live in 4 to 8 days. Catalogues with many product lines or dynamic bundling usually run $1,200 to $2,800.
How long before it is live?
4 to 8 days once we have your product catalogue and margin rules. Most of the time goes into deciding which combinations are actually worth suggesting.
Which tools does it connect to?
Shopify, WooCommerce and most checkout platforms, plus Telegram, WhatsApp and web chat for conversational upsells. Suggestions can also run as a post-purchase follow-up message.
What if the AI gets it wrong / is wrong?
The agent only suggests from a list your team approved, scored against what the customer already showed interest in. It never repeats a declined suggestion in the same conversation, and nothing gets pushed if there is no clear fit.
Is customer data safe?
The agent reads order and browsing data you already collect, never payment details. Every suggestion made, and its outcome, gets logged for review.