Elastic

How to integrate Elastic with Webflow

Elastic provides search and analytics capabilities that go beyond Webflow's built-in site search. Custom Elastic integrations add features like vector search, complex faceting, real-time analytics dashboards, and data pipelines that transform how visitors discover content and how you analyze site performance.

You can integrate Elastic with Webflow by embedding Kibana dashboards directly into pages using Code Embed elements, connecting the platforms through automation tools like n8n or Make.com, or building custom API integrations for full control over data synchronization and search functionality.

Embed Kibana dashboards with Code Embed

Kibana dashboards can be embedded directly into Webflow sites using HTML iframe snippets and the Code Embed element. This method works for displaying analytics visualizations, search performance metrics, and real-time data monitoring directly within your Webflow pages. The iframe supports customizable display options through URL parameters like show-top-menu, show-query-input, show-time-filter, and show-filter-bar to control which interface elements appear in your embedded dashboard.

You can generate the iframe code from Kibana's Share menu, which includes the embed=true parameter automatically. Configure display options through URL parameters to control which interface elements appear.

To implement Kibana embedding:

• Open your dashboard in Kibana and click Share to access embedding options
• Select Embed code to generate an HTML iframe snippet with your dashboard URL
• Copy the iframe code with your preferred display parameters configured
• Drag a Code Embed element onto your Webflow canvas from the Add panel
• Paste the iframe snippet and save your changes
• Add auth_provider_hint=anonymous1 to the URL for public dashboards without login requirements

Code Embed elements support up to 50,000 characters total across all custom code in your site. For larger embed code, host it externally and reference via <script src="..."></script> tags. Configure anonymous authentication in Kibana to let site visitors access dashboards without login credentials.

Connect with automation platforms

Middleware platforms like n8n.io and Make.com provide visual workflow builders for connecting Elastic and Webflow. These platforms support complex data transformations and bidirectional synchronization without custom code development.

n8n for workflow automation

n8n supports connecting Webflow with Elastic through native nodes for both platforms. The platform offers drag-and-drop workflow creation that connects Webflow triggers like form submissions and CMS item changes to Elastic actions including document indexing, updates, and search operations.

Build workflows in n8n that:

• Sync Webflow CMS items to Elastic indexes automatically using webhook triggers for collection_item_created, collection_item_changed, and collection_item_deleted events
• Transform data between Webflow's field structure and Elastic document schema by mapping text fields to Elastic text type, dates to date type, and references to keyword or nested types
• Handle authentication through API tokens and keys with Webflow using Bearer token authentication (with optional OAuth2) and Elastic using API keys or Basic authentication

Make.com for scenario building

Make.com supports both Webflow and Elastic through separate modules that you connect manually. Build custom scenarios that retrieve Webflow collection items, transform field data, and index documents to Elastic. Make.com does not provide pre-built templates for this integration, so you must construct the workflow from scratch.

Build workflows in Make.com that:

• Register Webflow collection triggers (collection_item_created, collection_item_changed, collection_item_deleted) to Elastic indexing actions
• Map field types between platforms through data transformation using Elastic's PUT /{index}/_mapping API
• Schedule bulk synchronization workflows using Elastic's POST /_bulk API for initial data migration
• Monitor workflow execution with Elastic query monitoring and Webflow webhook logging

Build with Webflow and Elastic APIs

Direct API integration gives you complete control over data synchronization, search implementation, and custom functionality. This approach works for advanced use cases like real-time content indexing, custom search UIs, and complex data transformation pipelines.

Sync CMS content to Elastic

Webflow's Collections API provides endpoints for retrieving and managing CMS content, while Elastic's Index API handles document storage and updates. Combine these to build automated synchronization that keeps your search index current with CMS changes.

Register Webflow webhooks for real-time synchronization instead of polling. According to Webflow's rate limits documentation, webhook-based architecture reduces API calls by over 90% compared to polling approaches, helping you stay within the 60-120 requests per minute limit.

Key implementation patterns include:

• Use POST /sites/{site_id}/webhooks from Webflow's webhook API to register for collection_item_created, collection_item_changed, and collection_item_deleted events
• Validate webhook payloads with HMAC-SHA256 signatures as documented in Webflow's webhook signatures guide
• Index documents to Elastic using PUT /{index}/_doc/{id} from the Elastic Document APIs
• Map Webflow field types to Elastic types by converting plain text fields to text with analyzer, dates to date with ISO 8601 format, numbers to integer or float, and slugs to keyword

For initial data migration, use POST /_bulk from Elastic's Bulk API to index multiple Webflow items simultaneously. This dramatically improves performance compared to individual index operations.

Implement exponential backoff for HTTP 429 rate limit responses from Webflow, respecting the Retry-After header. Check the errors field in Elastic bulk responses, as the bulk API returns HTTP 200 even when individual operations fail.

Build custom search interfaces

Elastic's Search API supports complex queries with filtering, faceting, and custom relevance scoring. Webflow's built-in Site Search feature is natively powered by Elastic, providing managed search capabilities without requiring custom integration. For custom search implementations, you can build middleware using platforms like n8n or Make.com, or develop custom API integrations.

Use GET /{index}/_search or POST /{index}/_search to query indexed content with JSON query DSL. The request body supports full-text search, filters, aggregations for faceted navigation, and highlighting for search result snippets.

Search implementation approaches include:

• Reference the Elastic Search UI library through <script> tags in Webflow Code Embed elements
• Build custom JavaScript that calls Elastic's REST API from the browser
• Create server-side search proxies to protect Elastic credentials and add custom logic
• Implement autocomplete with prefix queries and search-as-you-type functionality

Use Elastic API keys for programmatic access. API keys are preferred over HTTP Basic authentication for security. Avoid exposing credentials in client-side code by routing search requests through a backend service.

Process form submissions with data pipelines

Webflow's form submission webhooks trigger HTTP requests when users submit forms on your site. Connect these webhooks to Elastic to index form data, track submission patterns, and build analytics dashboards. This requires custom implementation using middleware platforms like n8n or Make.com, as no native Elastic-Webflow integration exists in the Webflow Marketplace.

Configure Elastic Ingest Pipelines to transform incoming webhook data before indexing. Pipelines support processors for data enrichment, field renaming, type conversion, and conditional logic.

Pipeline implementation includes:

• Create pipelines with PUT _ingest/pipeline/{pipeline_id} to define transformation rules
• Test pipeline configurations with POST _ingest/pipeline/{pipeline_id}/_simulate before production use
• Index documents to Elastic using the pipeline parameter with PUT /{index}/_doc/{id}?pipeline={pipeline_id}
• Build Kibana dashboards to visualize form submission patterns and conversion metrics

Validate incoming webhook signatures using HMAC-SHA256 as described in Webflow's webhook documentation.

What you can build

Integrating Elastic with Webflow lets you build advanced search experiences, automated content workflows, real-time analytics dashboards, and intelligent data synchronization between your CMS and search infrastructure.

• Advanced product search for e-commerce catalogs: Build search interfaces with fuzzy matching, faceted filtering by product attributes, and custom relevance tuning that surfaces the most relevant products based on user behavior and inventory data
• Real-time content indexing for publishing platforms: Sync blog posts, articles, and documentation from Webflow CMS to Elastic when editors publish new content, with custom search pages that query Elastic for full-text search with highlighting, related content recommendations, and filtered results by category or publication date
• Analytics dashboards embedded in client portals: Display Kibana visualizations showing website traffic, user behavior patterns, and conversion metrics directly within Webflow pages with anonymous authentication so clients view dashboards without separate login credentials
• Form submission analytics and lead scoring: Process Webflow form submissions through Elastic ingest pipelines that enrich data with geographic information, categorize submissions by intent, and calculate lead scores with Kibana dashboards that show submission volume by source, conversion rates, and demographic breakdowns for marketing optimization