HubSpot Blocks
HubSpot blocks provide comprehensive integration capabilities with the HubSpot CRM platform. These blocks enable you to read, write, and manage HubSpot data within your Ziggy flows.
Available HubSpot Blocks
Data Reading Blocks
- HubSpot Read - Read data from HubSpot objects
- HubSpot Get Associated - Retrieve associated records
- HubSpot Get All Owners - Get all HubSpot owners
- HubSpot Owner Translate - Translate owner references
Data Writing Blocks
- HubSpot Write - Create and update HubSpot records
- HubSpot Create Associations - Create relationships between records
- HubSpot Merge - Merge duplicate records
- HubSpot Timeline Write - Add entries to contact timelines
HubSpot Object Types
HubSpot blocks support the following object types:
- Contacts - Individual people and their information
- Companies - Business organizations
- Deals - Sales opportunities and transactions
- Tickets - Customer support requests
- Custom Objects - Your custom HubSpot objects
Authentication
HubSpot blocks require proper authentication:
- API Key: Your HubSpot API key for authentication
- Scopes: Appropriate permissions for the operations you need
- Rate Limits: Respect HubSpot's API rate limiting
Common Use Cases
- Data Migration: Import data from other systems into HubSpot
- Data Synchronization: Keep HubSpot data in sync with external systems
- Lead Processing: Automatically process and qualify leads
- Customer Onboarding: Automate customer setup processes
- Reporting: Extract data for analysis and reporting
Best Practices
- Batch Processing: Use batch operations for large datasets
- Error Handling: Implement proper error handling for API failures
- Rate Limiting: Respect HubSpot's API limits and implement backoff strategies
- Data Validation: Validate data before sending to HubSpot
- Testing: Test with small datasets before processing large amounts
Configuration Examples
Each HubSpot block can be configured with:
- Object Type: Which HubSpot object to work with
- Properties: Which fields to read or write
- Filters: Conditions for data selection
- Batch Size: Number of records to process at once
- Error Handling: How to handle failed operations