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, Facts) 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 3 destination systems that also function as sources:

Bi-Directional Sync

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

πŸ”„ Two-Way Sync

Configure the same system as both source and destination for true bi-directional synchronization.

  • β€’ Changes in either system sync to the other
  • β€’ Conflict resolution and deduplication
  • β€’ Maintains data consistency across platforms

🌐 Multi-System Sync

Use multiple sources feeding into multiple destinations for comprehensive data distribution.

  • β€’ Central data hub with multiple endpoints
  • β€’ Standardized data across all systems
  • β€’ Single source of truth maintenance

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) β†’ Outrun β†’ Salesforce (Destination)

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

Data Consolidation

Multiple Sources β†’ Outrun β†’ Single CRM (Destination)

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

Backup and Migration

Primary CRM (Source) β†’ Outrun β†’ Backup CRM (Destination)

Maintain backup systems or migrate between CRM platforms.

Multi-Regional Sync

Regional CRM (Source) β†’ Outrun β†’ 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
  • Salesforce: 10 requests per second for destination writes
  • Zoho CRM: 3 requests per 10 seconds for write operations

⚑ Performance Optimization

Outrun automatically optimizes destination writes with intelligent batching, retry logic, and rate limit management to ensure reliable data delivery.

Data Quality & Validation

Required Fields

Each destination has specific required fields that must be populated:

  • HubSpot: Email (People), Company Name (Organizations)
  • Salesforce: Email (People), Account 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

πŸš€ Add Your First Destination

Follow our step-by-step guide to configure your first data destination.

Get Started β†’

πŸ“₯ Browse Sources

See where you can get your data from to feed into destinations.

View Sources β†’

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