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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.”
Make.com’s 1,000 operation monthly limit severely constrains batch processing from Google Sheets to CRM systems, where each row read, data transformation, and API call consumes operations, limiting you to only 200-300 records monthly.
Here’s how to process thousands of records in bulk without artificial operation limits or per-record charges.
Process unlimited batches using Coefficient
Coefficient solves batch processing limitations by operating outside operation-based pricing models. Instead of counting individual record transfers, you get bulk data movements through native CRM connections without artificial limits.
How to make it work
Step 1. Set up scheduled bulk exports.
Configure automated exports that push entire datasets or filtered subsets to your HubSpot CRM on daily or weekly schedules. Process hundreds or thousands of records in single operations without per-record operation counting.
Step 2. Configure conditional batch logic.
Use Conditional Exports to process batches based on specific criteria like “Status = Ready for CRM” or “Date Added > Yesterday”. This intelligent batching processes only relevant records without consuming operations for filtering logic.
Step 3. Enable intelligent batch processing.
Turn on Coefficient’s UPDATE/INSERT logic to process entire batches while automatically handling duplicate detection and error recovery at the batch level. Failed records don’t break the entire batch operation.
Step 4. Implement bulk duplicate prevention.
Use native CRM duplicate detection that works across entire batches, not individual records. This prevents duplicate entries while processing large datasets efficiently without per-record validation costs.
Step 5. Set up batch monitoring.
Configure Slack and email alerts to notify you when batch operations complete, including detailed reporting on records processed, duplicates prevented, and any errors encountered during bulk processing.
Step 6. Scale batch size based on needs.
Whether you’re processing 50 records or 5,000 records, Coefficient doesn’t impose per-record charges or operation limits. Scale your batch processing based on business needs, not platform constraints.
Think batches, not operations
This approach transforms batch processing from a resource-constrained challenge into straightforward data management. You can focus on data quality and business logic rather than operation optimization, processing thousands of records as easily as dozens. Start processing unlimited batches today.
