Showing product recommendations on product pages

You can add a section to your product pages that displays an automatically-generated list of product recommendations. Displaying recommended products to customers makes it easier for them to discover new products, and can help to increase online store sales.

Products are recommended based on an algorithm that predicts the most relevant products based on the product a customer is interacting with. Here’s an example template of how recommended products could appear on a product page:

Recommended product placeholder example

The recommendation algorithm uses sales data and product descriptions to show a mix of products that are similar or often bought together. Product recommendations become more accurate over time as new orders and product data become available.

Before you add product recommendations to your theme, it's a good idea to be familiar with how the recommendations are generated, what their requirements and limitations are, and how you should implement them in your theme.

Recommendation logic

The algorithm that identifies recommended products is based on data about products that were purchased together and products with similar descriptions. It uses this data to provide a mix of those related products as recommendations for a given product.

In cases where purchase or product description data aren't available for a given product, products from a related collection are shown. The algorithm uses the collection in the URL from which the request to the API endpoint originated, and pulls other products from that collection. If the product doesn't have a collection URL, then the recommendation algorithm finds collections that include the product and pulls other products from those instead (excluding collections with handles “all” and “frontpage”).

Requirements and limitations

  • The types of product recommendations that appear are determined by your online store and your Shopify plan:

    • Purchase history and product descriptions: Plus plan and having <7000 products published in your Online Store, with an English storefront
    • Purchase history only: Plus plan and having <7000 products published in your Online Store, with a non-English storefront
    • Purchase history only: Non-Plus plan and having <7000 products published in your Online Store
    • Collections: Any plan with >7000 products published in your Online Store
  • You can't customize the recommendation algorithm to exclude specific products (but you can write custom JavaScript code where the recommendations are being displayed to exclude specific products).

  • The recommendation algorithm doesn't use orders that have been imported from another store or ecommerce platform to generate product recommendations.

  • Products that are out of stock, set to a price of 0, or gift cards aren't included in recommendations.

The following best practices can help to make sure that you're displaying recommended products in a way that improves the customer experience:

  • The recommendation algorithm associates up to ten products per individual product, in order of relevance. For example, the first recommended product is more relevant than the tenth recommended product. Because of this, it's a good idea to show no more than four products per product page to promote only the most relevant recommendations.
  • Make sure that you load the proper image size for the product card.
  • Because the recommendations are loaded asynchronously with JavaScript, you might want to add an empty state or not show the recommended products section at all. The placeholder is swapped with the actual recommended products after you load them.
  • Use phrases such as “You may also like” for the section header to explain to your customers why you're displaying the recommended products.

Tracking recommendations

After you've implemented product recommendations, you can track how effective they are directly from the Analytics page in your Shopify admin. To learn more about product recommendation reports, see Product recommendation conversion over time.

Next steps

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