Overview
Semantic Redirects use AI to understand the intent and meaning behind search queries, automatically directing customers to relevant pages instead of showing search results. Unlike keyword-based redirects, semantic matching understands variations and related terms, providing a more flexible and intelligent redirect experience. Semantic Redirects are managed through a dedicated settings page in the Layers dashboard under Settings → Semantic Redirects.How It Works
When a customer performs a text search, the system evaluates their query against your configured semantic redirects. If the query semantically matches a redirect term, the Search API returns a redirect URL instead of search results:- Customer searches for “customer service” or “need help”
- The system recognizes the semantic similarity to your configured “support” redirect
- The API returns a
_meta.redirectobject with the target URL - Your frontend navigates the customer to the support page
When Redirects Apply
Semantic redirects only trigger for text search requests. They do not apply to:- Image search
- Similar product search
- Browse/collection requests
Response Format
When a semantic redirect is triggered, the Search API response includes:- The
resultsarray is empty totalResultsis 0- The redirect URL is provided in
_meta.redirect.url
Common Use Cases
Customer Support Queries
Direct searches for help-related terms to your support page:- “help”, “support”, “customer service”, “contact us”
- Target URL:
https://yourstore.com/pages/contact-us
Brand Landing Pages
Route brand-specific searches to dedicated brand pages:- “nike”, “nike shoes”, “nike products”
- Target URL:
https://yourstore.com/collections/nike
Policy and Information Pages
Send policy-related queries to relevant information:- “return policy”, “returns”, “refund”, “how to return”
- Target URL:
https://yourstore.com/policies/refund-policy
Promotional Campaigns
Direct sale-related searches to campaign landing pages:- “sale”, “clearance”, “discount”, “deals”
- Target URL:
https://yourstore.com/collections/sale
Store Locations
Route location queries to store finder pages:- “store locations”, “find a store”, “stores near me”
- Target URL:
https://yourstore.com/pages/store-locator
Semantic Matching
The AI-powered semantic matching understands query intent beyond exact keywords:- “need help” matches a redirect configured for “customer service”
- “how do I return something” matches a redirect for “return policy”
- “where can I get support” matches a redirect for “help”
- “what’s on sale” matches a redirect for “clearance”
Configuration
Semantic Redirects are configured in the Layers dashboard:- Go to Settings → Semantic Redirects
- Click Create Redirect
- Enter the search terms that should trigger the redirect
- Provide the target URL (must be an absolute URL with protocol)
- Save and enable the redirect
Best Practices
Use broad terms - Configure redirects for general concepts rather than specific variations. The semantic matching will handle related queries. Provide absolute URLs - Always use full URLs including the protocol (https://) to ensure redirects work correctly. Test thoroughly - Use the Test Text Search tool to verify redirects trigger for expected queries and don’t activate unexpectedly for product searches. Monitor search analytics - Review which queries trigger redirects to identify gaps or opportunities for additional redirects. Consider the customer journey - Redirect to pages that help customers accomplish their goals, whether that’s finding information, getting support, or discovering products. Avoid over-redirecting - Don’t redirect queries that should show product results. Reserve redirects for informational queries, support requests, and specific landing pages.Beta Access
Semantic Redirects is currently in beta. Contact support to enable this feature for your account.See Also
- Create a semantic redirect - Step-by-step setup guide
- Search API - Technical documentation for the
_meta.redirectresponse field - Test text search - Testing and debugging search queries
- User intent processing - How search queries are analyzed