ADSX
NOVEMBER 5, 2026

Replace Basic Shopify Product Recommendations With AI and Free Tools

Use AI to draft a reviewed product-pairing map, then configure Search & Discovery. Compare this narrow workflow with Selleasy and calculate real savings.

AUTHOR
AT
AdsX Team
ECOMMERCE EDITORIAL
READ TIME
5 MIN
SUMMARY

Use AI to draft a reviewed product-pairing map, then configure Search & Discovery. Compare this narrow workflow with Selleasy and calculate real savings.

If you pay for an upsell app only to show a few accessories on product pages, start by checking Shopify Search & Discovery. AI can help prepare the pairings; Shopify's existing app can handle their display in a compatible theme. You do not need to build a new recommendation engine for a small, manually curated catalog.

This is a limited alternative to one function of Selleasy, not a replacement for its cart funnels, checkout placements or campaign management. The prompts below are illustrative and have not been executed against a merchant store.

Prepare verified product facts, review compatible pairings, then configure and inspect recommendations.
PREPARE VERIFIED PRODUCT FACTS, REVIEW COMPATIBLE PAIRINGS, THEN CONFIGURE AND INSPECT RECOMMENDATIONS.

Original AdsX illustration.

First check the free options

Shopify Search & Discovery is free. Selleasy also lists a free plan with up to five campaigns, so paying nothing may be possible without migrating. Its Starter plan currently lists $9 per month or $91 per year. Check your approved subscription and required features before using either price in a savings estimate.

Shopify's recommendations documentation distinguishes complementary items, bought alongside a product, from related items that can be substitutes. Your theme must support the relevant section or block. Recommended products must satisfy availability and publication requirements; a complementary product with no stock will not display even when continued selling is enabled.

Those are configuration constraints, not problems to solve with a larger AI prompt. Preview your theme before deciding that code is necessary.

Create a pairing sheet from product facts

Consider an illustrative camera-accessory store. A travel tripod can complement a camera only if its mounting and weight requirements match. A similarly priced tripod might be an alternative instead. An assistant should not infer compatibility from attractive names or pictures.

Main itemCandidateEvidence to supplyDecision
Camera bodyTripodVerified mount and supported loadReview as complementary
Travel tripodStudio tripodDifferent size and intended useReview as related
Camera bodyBatteryExact supported model listReject when model is unknown

Export only the product information needed: stable product identifier, title, URL, relevant specifications and merchant-approved compatibility notes. Customer records are unnecessary. Keep identifiers in the output so two similarly named products cannot be confused.

Prompt for a reviewable recommendation map

Using only this product table, propose up to three complementary products for each main product. Return the main identifier, candidate identifier, pairing reason, supporting source field and unresolved compatibility questions. Keep substitute products in a separate related-products table. Do not invent compatibility, purchase history, discounts or demand. If evidence is missing, mark the pairing needs review. Do not change the store. Start with ten products so I can inspect the reasoning.

Reject any row whose reason cannot be traced to supplied facts. The goal is to reduce clerical work while keeping merchandising judgment visible. A confident sentence is not compatibility evidence.

After review, configure the approved recommendations in Search & Discovery and enable their display in the theme. Preserve a copy of the previous setup. Do not import a large generated file until its identifiers and field mapping have been checked. Our AI app testing guide explains how to record evidence separately from an assistant's assurance.

Check the storefront before removing anything

Preview products with long names, multiple variants and no suitable pairing. Verify links and selected variants, phone layout, prices and the cart after adding an item. Remove or disable duplicate recommendation placements in a controlled way so shoppers do not see two competing widgets.

Also review a pairing when its accessory becomes unavailable. A recommendation list that looks sparse may reflect eligibility rules rather than a broken implementation. Keep a named owner responsible for new products, discontinued items and compatibility changes.

If your current app delivers bundles, discounts, cart offers or post-purchase offers, list those dependencies before uninstalling. A product-page list does not preserve them. Compare the broader responsibilities in when to keep a specialist app.

What could you save?

For twelve $9 Starter charges, the gross avoided charge is $108. In a hypothetical first year with two hours of setup and one hour of review at $40 per hour, labor is $120: the change costs $12 more before any incremental AI charge. Against a $91 annual subscription, it costs $29 more. An already-paid annual term may provide no immediate recoverable saving.

If the free plan covers the requirement, gross subscription savings are zero. If the replacement needs paid theme work, include it. Use the full-cost worksheet rather than treating the highest advertised app tier as your saving.

Keep the decision tied to the shopper's task

Use this workflow when a small set of checked accessory pairings is enough and the native display fits. Keep a maintained app when its additional placements, controls or support justify the cost. Evaluate changes over a comparable period using sales and margin, not merely clicks on the new widget. More recommendations do not establish more profit.

The merchant prompt library includes the pairing brief for reuse.

ABOUT THE AUTHOR
AT
AdsX Team
ECOMMERCE EDITORIAL

AdsX Team is the shared editorial byline for our Shopify and ecommerce publication. Guides combine primary sources with practical decision frameworks and clearly labeled examples. See our editorial policy for sourcing and corrections.

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