⚠️ This feature only works with Boost AI Search & Discovery V2 and above. To find out which version of our app you are using, please follow this article.
Understanding rule-based recommendation
Rule-based recommendations are generated by the rules set up by your store. The recommended products will be based on product attributes such as collection, vendor, tag, metafield, and product type.
Two types of recommendation widgets can use rule-based recommendations Frequently bought together and Related items.
Set up rule-based recommendation
As a basic flow to set up a recommendation widget, to create a rule-based widget in the app’s dashboard:
Go to Merchandising > Recommendation > Widgets.
Click Add new widget.
On the Recommendation Type section, select Product page or Cart page > select Frequently bought together or Related items > click Next.
⚠️ Currently, Rule-based recommendation is only available for Frequently Bought Together and Related items recommendation types.
4. On Recommended product settings, select Rule-based recommendation.
5. Toggle the desired rules to display recommended products. The recommended products will have the same attribute(s) as the source product.
Same collection (once enabled, you can select which collection to ignore)
Same product category
Same product type
Same vendor
Same tags (once enabled, you can select which tags to ignore)
Same product metafield value 1-3
The list of product metafields is linked to the metafields added on the Tool > Metafields feature. Remember to sync recent updates when you add a new metafield from Tool > Metafields.
Once enabled, you can choose which metafield values to ignore.
You can also rearrange the rules list by simple drag-and-drop method:
⚠️ The maximum number of rules that can be enabled at the same time is 4.
💡 When multiple rules are enabled, it will apply logic OR. The more rules a recommended product matches to the source product, the higher the ranking.
To change the rule priority, you can drag and drop the selected rules. The highest rule will be considered to show the products matching this rule in the first position on the storefront.
Example:
You are enabling two rules: same collection (1st) and same vendor (2nd)
→ All products that match the same collection and vendor will be considered as recommended products.
Products in the same collection as the source product will appear first in the recommended products list.
After that, products from the same vendor as the source product will be displayed.
We have ignored fields so that you can exclude specific collections, tags, and metafields from the model. The input data for the model will not include these ignored values.
Example:
The source product has 3 tags A, B, and C. Then you ignore tag B ⇒ The Model will understand that the source product only has tags A and C → it will recommend the products that have the same tags A and C as the source product.
6. Click Next.
7. Start customizing your recommendation widgets.
Tutorial Video
Watch our tutorial video to learn how to set up a Product Recommendation Widget:
Feel free to reach out to our dedicated support team via chat if you have any questions or require additional assistance.