Recombee AddBookmark
Overview
This node records when a user bookmarks an item in a recommendation system. Bookmarks represent strong user interest and help improve the accuracy of personalized recommendations by signaling which items users have saved or favorited. The node is useful for tracking user engagement with content, products, or other entities in applications such as e-commerce, media platforms, or content management systems.
Typical use cases include:
- Logging when a user saves a product to a wishlist.
- Tracking articles or videos a user has favorited.
- Associating bookmarks with specific recommendation campaigns or contexts.
The node supports batch processing of multiple bookmark events, retrying failed requests to handle temporary network issues or rate limits.
Properties
| Name | Meaning |
|---|---|
| User ID | The ID of the user who bookmarked the item. |
| Item ID | The ID of the item that was bookmarked. |
| Cascade Create | Whether to create the item if it does not exist in the database (true/false). |
| Timestamp | Optional timestamp of when the bookmark was created. If not provided, the current time will be used. |
| Max Retries | Number of times to retry failed batch requests. Useful for handling temporary network issues or rate limits. |
| Recommendation ID | Optional recommendation ID. If provided, the bookmark will be associated with this specific recommendation. |
Output
The node outputs an array of JSON objects, each representing the result of adding a bookmark:
success: Boolean indicating whether the bookmark was successfully recorded.error: Present only if the operation failed; contains error details.- Other fields: Echoes input parameters (
userId,itemId,recommId,cascadeCreate,timestamp) for reference. data: Contains additional response data from the API when successful.
If the node is configured to continue on failure, errors for individual bookmarks are included in the output without stopping execution. Otherwise, the node throws an error on the first failure.
The node does not output binary data.
Dependencies
- Requires an external recommendation service API client.
- Needs credentials including:
- Database identifier
- Private token for authentication
- Region specification
- API timeout setting (optional)
- The node batches requests up to 100 bookmarks per batch to optimize performance.
Troubleshooting
Common Issues:
- Network failures or rate limiting may cause batch requests to fail.
- Invalid user or item IDs can lead to errors from the recommendation service.
- Missing or incorrect credentials will prevent API access.
Error Handling:
- The node retries failed batch requests up to the configured maximum number of retries.
- If "continue on fail" is enabled, errors for individual bookmarks are reported in the output but do not stop the entire execution.
- Without "continue on fail," the node throws an error immediately upon failure.
Resolution Tips:
- Verify all required properties are correctly set.
- Ensure credentials are valid and have sufficient permissions.
- Adjust "Max Retries" to handle transient network issues.
- Use timestamps in ISO format or leave empty to use the current time.