Destinations

Destinations

Destinations are where your standardized data goes. Outrun takes the clean, standardized objects from your sources and delivers them to your chosen destinations, enabling powerful bi-directional sync scenarios.

How Destinations Work

When you configure a destination in Outrun:

1. Data Reception - Standardized objects (People, Organizations, Relationships) arrive from sources
2. Field Mapping - Outrun maps standardized fields to destination-specific fields
3. Validation - Data is validated against destination requirements and constraints
4. Delivery - Clean data is written to your destination system via APIs

Supported Destinations

We currently support 8 destination systems:

Also Available

The following destinations are supported and available in the app:

• Salesforce - Contacts, Leads, and Accounts
• Intercom - Contacts and Companies
• Zendesk Support - Users and Organizations
• Zoho Desk - Contacts and Accounts

Bi-Directional Sync

All our destination systems also function as sources, enabling powerful bi-directional sync scenarios:

Destination Capabilities

Field Mapping

• Automatic Mapping: Smart defaults for common field mappings
• Custom Mapping: Configure specific field transformations
• Required Fields: Automatic validation of destination requirements
• Data Types: Proper type conversion and validation

Data Validation

• Schema Validation: Ensure data meets destination requirements
• Constraint Checking: Validate against picklists, formats, and rules
• Error Handling: Graceful handling of validation failures
• Retry Logic: Automatic retry for transient failures

Performance Optimization

• Batch Processing: Efficient bulk operations where supported
• Rate Limiting: Respect destination API limits
• Incremental Updates: Only send changed data
• Conflict Resolution: Handle duplicate and conflicting data

Common Use Cases

CRM Synchronization

HubSpot (Source) → Outrun → Zoho CRM (Destination)

Keep your CRM systems in sync with standardized contact and company data.

Data Consolidation

Multiple Sources → Outrun → Single CRM (Destination)

Consolidate data from multiple systems into a single CRM for unified management.

Backup and Migration

Primary CRM (Source) → Outrun → Backup CRM (Destination)

Maintain backup systems or migrate between CRM platforms.

Multi-Regional Sync

Regional CRM (Source) → Outrun → Global CRM (Destination)

Sync regional data to global systems while maintaining local operations.

Rate Limiting & Performance

Each destination has specific rate limits that Outrun respects:

• HubSpot: 10 requests per second for destination writes
• Zoho CRM: 3 requests per 10 seconds for write operations

Data Quality & Validation

Required Fields

Each destination has specific required fields that must be populated:

• HubSpot: Email (People), Company Name (Organizations)
• Zoho CRM: Last Name (People), Account Name (Organizations)

Data Transformation

• Field Mapping: Automatic mapping between standardized and native fields
• Type Conversion: Proper data type handling (strings, numbers, dates)
• Format Validation: Email, phone, URL format validation
• Constraint Checking: Picklist values, field length limits

Error Handling

• Validation Errors: Clear reporting of field validation failures
• Retry Logic: Automatic retry for transient API failures
• Conflict Resolution: Handle duplicate records and data conflicts
• Monitoring: Real-time sync status and error reporting

Best Practices

Setup Recommendations

1. Authentication: Use dedicated service accounts for destinations
2. Field Mapping: Review and customize field mappings for your use case
3. Required Fields: Ensure source data includes all required destination fields
4. Testing: Start with small data sets to verify mappings and behavior

Performance Optimization

1. Batch Size: Configure appropriate batch sizes for your data volume
2. Sync Frequency: Balance real-time needs with API rate limits
3. Selective Sync: Only sync necessary objects and fields
4. Monitoring: Set up alerts for sync failures and performance issues

Data Quality

1. Source Validation: Ensure clean data at the source level
2. Mapping Validation: Test field mappings with sample data
3. Duplicate Handling: Configure appropriate deduplication strategies
4. Error Monitoring: Regularly review sync errors and data quality issues

Next Steps

Need a destination that's not listed? Contact us to discuss custom integrations.