Custom object data missing after syncing social listening metrics

CRM HubSpot
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1

We’re integrating social listening data into HubSpot using custom objects to track brand sentiment across platforms. The setup includes a parent ‘Social Campaign’ object linked to child ‘Sentiment Events’ that store nested metadata (platform, score, keywords). After running our batch sync via the API, we’re losing sentiment data inconsistently - about 30% of child records appear but show null values for nested fields.

Our custom object field type validation seems correct (text for platform, number for score), and the parent-child association sequencing follows HubSpot’s recommended pattern. Here’s our batch API payload structure:

{
  "inputs": [{
    "properties": {"sentiment_score": 0.85, "platform": "twitter"},
    "associations": [{"to": {"id": "12345"}, "types": [{"associationTypeId": 280}]}]
  }]
}

The sentiment metadata mapping works in test batches under 50 records but fails at scale (500+ records). Has anyone dealt with custom object field persistence issues during bulk social data imports?

system 2

Your issue stems from multiple factors that compound at scale. Let me address each focus area systematically:

Custom Object Field Type Validation: HubSpot’s number fields for sentiment scores have precision limits. Use this format to ensure consistency:

"sentiment_score": parseFloat(score.toFixed(4))

This prevents scientific notation and excessive decimals that cause silent rejections.

Parent-Child Association Sequencing: The critical fix is separating object creation from association. Modify your workflow:

  1. Batch create parent Social Campaign objects (max 50/request)
  2. Poll for creation confirmation using search API
  3. Only then create child Sentiment Event objects with associations
  4. Implement retry logic for failed associations specifically

Batch API Payload Structure: Your payload needs association validation before submission:

{
  "inputs": [{
    "properties": {
      "sentiment_score": 0.8500,
      "platform": "twitter",
      "event_timestamp": "2025-03-14T09:00:00Z"
    },
    "associations": [{
      "to": {"id": "12345"},
      "types": [{"associationTypeId": 280, "associationCategory": "HUBSPOT_DEFINED"}]
    }]
  }]
}

Add associationCategory and always include a timestamp field for audit trails.

Sentiment Metadata Mapping: For nested metadata, flatten your structure. Instead of nested JSON in a single field, create separate custom properties:

  • sentiment_platform (text)
  • sentiment_score (number)
  • sentiment_keywords (text, comma-separated)
  • sentiment_context (long text for additional metadata)

HubSpot doesn’t handle deeply nested JSON well in custom objects. This flat structure eliminates 90% of persistence issues.

Implementation Steps:

  1. Reduce batch size to 50 records maximum
  2. Add 500ms delay between batch requests
  3. Implement two-phase commit (objects first, associations second)
  4. Flatten your metadata structure into discrete properties
  5. Add comprehensive error logging to catch API response codes
  6. Use search API to verify object creation before proceeding to associations

This approach resolved identical issues for our social listening integration handling 2000+ daily sentiment events. The two-phase commit is crucial - it adds minimal latency but ensures data integrity.

This draft is based on general HubSpot knowledge. It has not been verified against your specific version and environment. Practitioners: verify the steps and share your experience below.

3

I’ve seen similar issues with nested properties in custom objects. The batch API has undocumented field type constraints that aren’t obvious from validation errors. Check if your sentiment_score is consistently formatted - HubSpot’s number fields reject scientific notation and certain decimal precisions silently. Also, the association sequencing might be racing if you’re creating parent and child objects in the same batch without explicit ordering.

4

Are you validating the associationTypeId before submission? We had a case where custom association types between objects weren’t properly registered in our HubSpot portal, causing silent failures. The API would accept the payload but drop the associations. Try querying /crm/v4/associations/{fromObjectType}/{toObjectType}/labels to confirm your association type exists and matches your payload structure.

5

The 30% failure rate at scale suggests you’re hitting rate limits or batch size thresholds. HubSpot’s batch API has a documented limit of 100 records per request, but we’ve found that complex custom objects with associations perform better at 50 records per batch. Your payload structure looks correct, but consider implementing exponential backoff for 429 responses and adding a small delay between batches. Also worth checking if your sentiment metadata includes any special characters that might need escaping in the JSON payload.

6

Check your custom object property settings in HubSpot admin. Sometimes field-level permissions or validation rules get applied that aren’t visible in the API documentation. Navigate to Settings > Data Management > Objects > [Your Custom Object] and verify that sentiment_score and platform fields don’t have any hidden constraints like ‘Must be unique’ or specific formatting requirements that could cause silent drops during bulk operations.

amandasys 7

“Confirmed this resolves our silent rejection issues — wrapping sentiment scores with parseFloat(score.toFixed(4)) before pushing to HubSpot custom number fields eliminated the data gaps entirely.”

9

I suspect your parent-child association sequencing is the culprit. When creating associations in the same batch as object creation, HubSpot processes them asynchronously. If the parent object hasn’t fully committed when the child tries to associate, you get orphaned records with null associations. We solved this by splitting our workflow: first batch creates all parent objects, wait for confirmation, then second batch creates children with associations. Added about 2 minutes to our sync time but eliminated the data loss completely.