Free tools Windows power users keep installed
One-click scans. No signup required.
Improve cart suggestions by showing a small number of clearly relevant products that complement what a shopper has already chosen. Explain why each item appears, make compatibility clear, and measure the effect on cart and checkout outcomes rather than assuming recommendations increase sales.
What makes a cart suggestion useful?
A useful cart suggestion helps shoppers complete or get more from their current choice. If someone adds a camera, for example, a compatible memory card may be a better suggestion than another camera. The recommendation should fit the shopper’s apparent intent, not simply reflect what other customers happened to buy.
As an Amazon Associate I earn from qualifying purchases.
Relevance matters because a weak suggestion can undermine confidence in the rest of the store’s recommendations. In a Baymard Institute benchmark published on January 12, 2021, 52% of the desktop sites benchmarked showed cart or added-to-cart cross-sells that were completely irrelevant or based only on other customers’ purchases. That is a finding about the sites in that benchmark, not an estimate for all ecommerce stores today. Baymard Institute’s cart cross-sell guidance explains the underlying usability concerns.
Recommended Free Tools
Which products should you recommend in the cart?
Prioritize complements over alternatives
Complements work with, complete, or enhance something already in the cart: a compatible charger, an ingredient used with a food product, or a case designed for the selected device. Alternatives are different versions of the item the shopper already chose. Near checkout, alternatives can prompt reconsideration and divert attention from completing the order; make complementary items the default focus instead. Baymard’s advice on cart cross-sells covers this distinction.
#1 Best Overall
Use compatibility and context as filters
For products where fit or compatibility matters, verify the match before showing it and state the relevant compatibility plainly. Use the current cart, the browsing session, purchase history, customer profile, and product-category relationships where appropriate. Co-purchase patterns can help, but they should not be the only signal: products bought together are not necessarily useful or compatible for this particular shopper.
Show only the strongest matches
Do not fill a fixed number of recommendation slots just because the design has room. If only one or two products genuinely fit, show one or two. A short, relevant list is easier to scan and helps protect trust in future suggestions.
How should you label and present suggestions?
Give shoppers an accurate reason for each recommendation. Labels such as “Pairs well with” or “Frequently bought together” are useful only when they describe the logic actually used. If a product appears because of browsing history, say so only when that signal drove the recommendation. When compatibility is important, put the specific fit information where shoppers can see it rather than relying on a vague label.
Rank #2
Match any promotion to the shopper’s context. A discount does not make an irrelevant product relevant, and a promotional message should not obscure why the item belongs with the cart. Baymard’s guidance recommends clear labels, relevant themes, compatibility-aware choices, and context-sensitive promotions. Read the Baymard guidance.
Which recommendation approach should you use?
Choose an approach based on the quality of its product logic and the control it gives your team—not on a promise of higher revenue. The main options are platform-native recommendations, manual curation, and third-party apps.
Platform-native recommendations
For Shopify stores, the Storefront API’s productRecommendations query returns recommendations for a product and accepts a recommendation intent. Shopify says its automatically generated related recommendations use sales data, product descriptions, and collection relationships. Complementary recommendations require manual configuration in Shopify Search & Discovery. The API can return up to ten Product objects. Shopify’s Storefront API documentation describes the query.
Rank #3
- Used Book in Good Condition
Shopify’s guide to complementary products describes products often bought in addition to a selected product. It recommends showing two to three by default on product pages and paginating additional items. It also says the API excludes out-of-stock items, zero-price products, gift cards, and products already in the visitor’s cart. This guide concerns product pages; confirm that your theme and cart surface support the same component before relying on it in-cart. Shopify’s complementary-product guide has the configuration details.
The Tool Desk
Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Manual curation
Curated recommendations can work well when product compatibility or use is difficult to infer from sales patterns alone. Set rules for which items pair together, exclude unsuitable products, and review the pairings when your catalog changes. This approach gives your team direct control, but it requires maintaining accurate relationships.
Third-party apps
Apps may support placements such as a cart page or drawer, checkout, or a post-purchase screen, but features and analytics vary. Check whether an app understands compatibility and complementarity, lets you control exclusions and labels, works with your theme without slowing the experience, and tracks the placement you intend to test. Shopify’s App Store has a category for frequently-bought-together and upsell or cross-sell apps; listings can change, and marketplace descriptions or ratings are not independent evidence of results. Browse Shopify’s app category.
Rank #4
Compare implementations on the details that affect shoppers
- Recommendation logic: Does it distinguish complementary products from mere co-purchases and alternatives?
- Control: Can you set exclusions, cap the number of items, and use accurate labels and offers?
- Placement: Does it support the actual surface you want, such as the cart page or cart drawer?
- Integration: Does it work with your theme and preserve a fast, usable cart?
- Measurement: Can you track views, clicks, adds, purchases, cart value, and checkout progression for that placement?
How can you measure whether cart suggestions work?
Measure both the recommendation funnel and the checkout experience. A click or add-to-cart indicates engagement, but does not by itself establish that the recommendation caused a purchase or improved the business outcome.
Track the recommendation funnel
Shopify’s Behavior Reports documentation describes measures for sessions with recommendations, sessions with recommendation clicks, sessions with recommendation add-to-carts, and sessions with purchases, along with click, add-to-cart, and purchase rates. Recommendations must use the URL format specified by Shopify’s API to be tracked. The report excludes products added to cart or purchased through Buy Button or a third-party app, and it may omit engagement from the preceding 24 hours. Its low-engagement report uses the last 30 days of data and updates daily. See Shopify’s Behavior Reports documentation.
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
Evaluate cart and checkout outcomes
For a cart-specific change, also track total cart value and checkout progression or completion. Choose a baseline period, then compare the changed experience with a control when feasible, keeping other material changes steady. Add experience guardrails that fit your store, such as dismissals or customer complaints. Attribute revenue carefully if some cart interactions occur through channels excluded from the platform’s recommendation report.
Quick Recap
A practical launch checklist
- Define the shopper’s task: Decide what a relevant complement helps them do with the item already in the cart.
- Set pairing and exclusion rules: Confirm compatibility, remove unsuitable products, and avoid presenting alternatives as the default near checkout.
- Choose the placement and logic: Verify that your native feature, curated rules, or app supports the specific cart surface you use.
- Set a relevance threshold: Show fewer items rather than filling slots with weak matches.
- Write truthful labels: Explain the real reason for each suggestion and include fit information where it matters.
- Validate tracking: Check that views, clicks, adds, and purchases are recorded for the implementation and account for reporting exclusions.
- Test against a baseline: Compare cart value and checkout completion as well as recommendation engagement, and review the results before expanding the treatment.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
