Refine recommendations with rules

Recommend rules are if-then statements that let you refine and curate your recommendations without editing code. When a condition (if) is met, the rule’s consequences (then) are applied to the recommendations.

The number of rules you can apply to a recommendation scenario depends on your Algolia plan.

Examples

Examples for rules include:

• Show related products from the same category as the viewed product. Create a rule “Boost items” as consequence, where you select the category attribute and the sameAsViewedItem value. This doesn’t exclude recommendations with different categories, which can be helpful if you have categories with only few recommendations.

• Exclude recommendations for out-of-stock products. For example, if your index has an inventory attribute as count, you can create a rule with “Filter items” as consequence, where you select inventory > 0 as filter condition. This excludes all recommendations with 0 or undefined inventory.

• Curate recommendations by pinning them. For example, if you want to make best sellers or newly launched items show up first as recommendations, create a rule with the “Pin items” consequence and select specific items and their position in the list of recommendations.

• For all products from a specific category, boost items of a specific type. For example, in the category “hair” (category:hair), recommend all shampoos (product_type:shampoo) first. Create a rule with the “Subset of source items” condition and select “category is hair”. Add a “Boost items” consequence with “product_type is shampoo”.

Add rules to recommendations

1. Go to the Algolia dashboard and select your Algolia application.

2. On the left sidebar, select Recommend.

3. On the Rules page, select the index and model to which you want to apply rules.

   

   You can apply rules to trained Frequently Bought Together and Related Product models.

4. Click + New rule and select the conditions when the rule should apply.

   • Any item is a source item. The consequences of this rule apply to all recommendations.
   • Specific item is viewed. The consequences of this rule apply only when recommendations for a specific item are retrieved.
   • Subset of source items. The consequences of this rule apply to items that match a filter.

5. Optional: add a context for this rule. Contexts are additional constraints for rules. For more information, see Context-only rules.

6. Under Consequence(-s), click Add consequence and select what to do when the conditions are met:

   • Pin items. Put one or more selected items at a specific position in the list of recommendations (1 is first)
   • Hide items. Exclude one or more selected items from the list of recommendations.
   • Boost items. Enter filter criteria and show matching items before non-matching items in the list of recommendations.
   • Bury items. Enter filter criteria and show matching items after non-matching items in the list of recommendations.
   • Filter items. Enter filter criteria and only include matching items in the list of recommendations.

   To only show items with the same attribute value as the viewed item, set the value to sameAsViewedItem.

   

7. Optional: add a description for the rule and select a timeframe, when the rule should be active.

Rules precedence algorithm

Algolia uses the following tie-breaking algorithm to determine which rules should apply first:

1. Rules for which you’ve specified a context.
2. Rules with Filter items, Boost items, or Bury items consequences.
3. Rules with a specified validity time frame.
4. If there are still tied rules, the one with the lowest object ID (alphabetically ordered) wins.