Glossary
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product-recommendation
E-commerce product recommendation: definition of a recommendation engine, vs cross-selling and upselling, Shopify Search & Discovery, and AOV best practices.
Updated on
June 4, 2026
A recommended product is an item offered to the visitor because it is highly likely to complement their need, capture their interest, or help them continue browsing. The recommendation can appear on a product page, in the shopping cart, on the home page, or in a post-purchase email. Its role is not only to push an additional sale: it also serves to guide the customer through the catalog, make the store more readable, and increase the average order value when the suggestions are genuinely relevant.
Summary
Definition of the recommended product in e-commerce
In an online store, a recommended product is a suggestion presented to the customer at the right moment in the purchasing journey. This suggestion can be chosen manually by the merchant, calculated automatically by a recommendation engine, or built from a mix of business rules and behavioral data. For example, a product page dedicated to a pair of shoes might suggest technical socks, an institutional spray, or a similar model in another color.
Product recommendation should not be confused with simple commercial promotion. A banner presenting a new arrival to all visitors is more akin to catalog merchandising. A recommendation block, on the other hand, seeks to establish a logical link between the browsing context and the suggested products. This link can be very direct, like a complementary accessory, or more subtle, like a product frequently viewed by customers with the same profile.
A distinction is generally made between several categories of recommendations. Complementary products fall under cross-selling, as they add something to the main product. Similar products help the customer compare close alternatives. Best sellers provide reassurance through social proof, while personalized recommendations rely on browsing history, previous purchases, or detected preferences. In any case, the value of a recommendation depends less on the number of products displayed than on the quality of the choices offered.
Why recommended products are important for an online store
Recommended products are important because a customer never browses an entire catalog. Even in a well-organized store, a large portion of references remains invisible if the visitor does not already know they exist. Recommendation then acts like a discreet salesperson: it highlights useful items, gives ideas, and reduces the effort needed to find the right product.
For the merchant, the benefit is twofold. On one hand, recommendations can improve the AOV by adding accessories or complementary products to the cart. On the other hand, they streamline the user experience by avoiding long searches, backtracking, or unnecessary hesitation. A good recommendation does not feel like a forced sale; it feels more like contextual help.
This logic becomes particularly useful for wide catalogs, fashion, beauty, sports, decor, or technical equipment stores. In these areas, the customer may need to be guided between multiple variants, price ranges, or uses. Conversely, a poorly thought-out recommendation can have the opposite effect: offering an out-of-stock item, an overly expensive product, or a competing alternative to the main product risks causing confusion and weakening trust.
Recommendation type | Main benefit |
|---|---|
Complementary product | Increase the average order value with a coherent accessory. |
Similar product | Help the customer compare before choosing. |
Best seller | Reassure through the popularity of the product. |
Personalized recommendation | Adapt the experience to the visitor's behavior. |
How it works on Shopify and points of vigilance
On Shopify, recommendations can be managed in several ways. The Search & Discovery app notably allows for configuring complementary or related products, while many Online Store 2.0 themes already have sections designed to display recommended items on product pages or in the cart. Specialized apps go further by using purchase history, product combinations, or more advanced merchandising rules.
The main point of vigilance concerns relevance. It is better to display four perfectly consistent products than a carousel of twelve approximate items. The merchant must also monitor stock, margin, and block placement. On mobile, a recommendation placed too low can remain invisible; in the cart, an excess of suggestions can slow down the decision instead of encouraging it.
Performance is measured with a few simple indicators: click-through rate on the block, cart additions from recommendations, associated revenue, and the evolution of the average order value. This data allows for adjusting titles, product order, and selection rules without being limited to a subjective impression.
In brief
A recommended product is a contextualized suggestion that helps the customer discover a relevant item during their shopping journey. When used well, recommendations improve navigation, increase basket value, and make the catalog feel more alive. However, they must remain coherent, measured, and useful: the best recommendation is one that gives the customer the impression of having found exactly what they needed.
Associated terms, FAQ, and going further
Associated terms
To better understand this topic, it is useful to associate it with the following concepts:
FAQ
Is a recommended product always a cross-sell?
No. Cross-selling seeks to sell a complementary product, whereas a recommendation can also suggest a similar product, a best seller, or a personalized selection.
How many products should be recommended?
It is better to limit the number of suggestions and prioritize relevance. A small, clear block often works better than a long, inconsistent carousel.
Go further
This sheet can be linked to other glossary content in order to build a coherent internal linking structure around the purchasing journey, conversion, e-commerce operations, and customer experience.
In brief
Recommended product = SKU suggestion based on visitor context.
Types: associated, similar, best-sellers, personalized.
Distinct from cross-sell (tactic), upsell, bundle, filters.
Levers: AOV, discovery, conversion, stock clearance.
Shopify: Search & Discovery, theme, AI apps, email.
Relevance, click-through and AOV measurement, manual curation of top SKUs.
Associated terms, FAQ, and going further
Associated terms
Cross-sell: tactic complementing the main product.
AOV: KPI often boosted by recommendations.
Product page: key location for recommendations.
Cart page: pre-checkout recommendation area.
E-commerce analytics: measuring block performance.
FAQ
Recommended product and cross-sell: what is the difference?
The recommended product is the displayed suggestion (block, widget, email). Cross-selling is the commercial intent: selling a complement. All cross-selling goes through a recommendation, but a recommendation can also show similar items or best-sellers.
Does Shopify handle recommendations natively?
Yes via Search & Discovery (related, complementary products) and theme sections. For advanced rules or AI, third-party apps complement the native features.
Are recommendations needed on every product page?
Recommended on high-traffic PDPs (best-sellers, landing ads). On highly niche SKUs with no complement, a "similar products" or category best-sellers block is sufficient.
How to measure the effectiveness of a recommendation block?
Track the click-through rate, cart additions from the block, and the AOV of sessions where the widget is visible. Compare over 2 to 4 weeks before/after the change.
Going further
Sources: Shopify Help Center (Product recommendations), Add product recommendations to theme.
Enzo
June 4, 2026
