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“Supermetrics is a Bitter Experience! We can pull data from nearly any tool, schedule updates, manipulate data in Sheets, and push data back into our systems.”
HubSpotInconsistent refresh schedules betweenand Google Sheets typically happen because of API rate limiting, authentication expiry, or conflicting schedules that cause some imports to fail while others succeed.
Here’s how to diagnose these issues and implement a reliable scheduling system that eliminates refresh failures and timing conflicts.
Common causes of refresh schedule failures
API rate limiting is the most frequent culprit – HubSpot’s API limits can cause scheduled refreshes to fail or queue up when multiple imports try to run simultaneously. Large datasets may exceed processing time limits, causing timeouts that look like schedule failures. OAuth tokens can expire without proper renewal, and multiple imports competing for resources create conflicts that affect reliability.
Time zone confusion also plays a role. Schedules might execute at unexpected times if your connector and HubSpot account use different timezone settings, making it appear that refreshes are inconsistent when they’re actually running on the wrong schedule.
Immediate troubleshooting steps
Step 1. Check error logs and API usage.
Look for specific failure messages in your connector’s error logs. Verify that your API usage hasn’t exceeded HubSpot’s daily limits. Test with smaller data sets to isolate whether timeout issues are causing apparent schedule failures. Document actual vs expected refresh times to identify patterns.
Step 2. Re-authenticate and verify timezone settings.
Re-authenticate your HubSpot connection if refresh failures persist – expired tokens are a common cause of intermittent failures. Check that your connector, Google Sheets, and HubSpot account all use the same timezone settings to ensure schedules execute when expected.
Reliable scheduling with intelligent conflict management using Coefficient
Coefficientsolves refresh reliability issues through intelligent schedule management and automatic conflict resolution. Each import has its own independent schedule, preventing cascade failures where one failed import affects others. The system automatically staggers execution to avoid API limits and includes retry logic for failed refreshes.
The key advantage is comprehensive monitoring with alerts for both successful completions and failures, plus predictive warnings when you’re approaching API limits.
How to make it work
Step 1. Set up staggered scheduling to prevent conflicts.
Install Coefficient and create your HubSpot imports. For hourly refreshes, set your primary import to run at :05 past the hour, secondary imports at :15, :25, etc. This prevents multiple large imports from competing for API resources simultaneously. Use the “Skip if running” option to prevent overlaps if an import takes longer than expected.
Step 2. Configure intelligent retry and monitoring.
Enable automatic retry logic so failed refreshes attempt again without manual intervention. Set up email or Slack alerts for both successful completions and failures with specific error details. Create snapshot backups of critical data so you have fallback options if refreshes fail during important reporting periods.
Step 3. Implement large dataset handling strategies.
For datasets over 10,000 rows, break them into multiple filtered imports that run on staggered schedules. Use incremental refresh with “Append New Data” to reduce processing time and API usage. Schedule heavy imports during off-peak hours when API limits are less likely to be reached.
Step 4. Set up comprehensive monitoring and alerts.
Configure alerts for refresh failures with error details, successful completions for critical imports, data anomalies like unexpected row count changes, and schedule execution confirmations. Create a dashboard that shows last refresh time and next scheduled update for all your imports.
Stop worrying about data refresh reliability
Try CoefficientConsistent data updates shouldn’t require constant monitoring and manual intervention.to eliminate the scheduling conflicts and API issues that cause inconsistent HubSpot data refreshes.
