Suggestion Rules
Suggestion rules let you set persistent, automated logic for which suggestions appear on product pages. Instead of relying entirely on AI-generated suggestions or editing pages one by one, you can define rules that match against your catalog data and apply to every product that fits your criteria, now and in the future.
What’s new
Rule-based suggestion matching: Define conditions using product tags, categories, or custom attributes, and pair them with specific suggestions. When a visitor lands on a matching product page, those suggestions appear automatically.
Composable condition builder: Build rules with up to five conditions joined by AND/OR logic. The condition builder auto-populates with your actual catalog facets, so you're always working with real data.
Priority ordering with drag-and-drop: Rules are evaluated in order, and the first match wins. Reorder them with drag-and-drop to control which rules take precedence.
Graceful AI fallback: When no rule matches a product page, the system falls back to AI-generated suggestions. Rules and AI work together, not as a replacement.
Why we made these changes
For brands with large catalogs, editing suggestions page by page doesn't scale. A store with thousands of products needs a way to say "for all shoes tagged Summer, show these suggestions" without touching each page individually. Suggestion rules solve that by letting you express intent at the catalog level. They apply retroactively to existing products and automatically cover new ones that match your criteria, which means your suggestions stay relevant as your catalog grows.