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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.”
HubSpot forces you to merge contacts one at a time through the UI, and the duplicate management tool has serious restrictions on bulk operations that make large-scale deduplication painfully slow.
Here’s how to handle bulk deduplication at scale while preserving data integrity and creating an audit trail of your merge decisions.
Process thousands of duplicates systematically using Coefficient
Coefficient provides a powerful workaround for large-scale deduplication by connecting your HubSpot contacts to spreadsheets where you can identify duplicates using formulas, consolidate data systematically, then execute bulk updates and deletions back to HubSpot . This handles deduplication at enterprise scale with capabilities not available in HubSpot’s native tools.
How to make it work
Step 1. Export and identify duplicates using spreadsheet formulas.
Import all contacts with key identifying fields like email, name, company, and phone. Use =COUNTIF($A:$A,A2)>1 to flag duplicate emails, or =CONCATENATE(B2,C2,D2) to create unique identifiers for fuzzy matching. Apply conditional formatting to highlight duplicate sets visually.
Step 2. Consolidate data from duplicate records systematically.
Use VLOOKUP or INDEX/MATCH formulas to merge data from duplicate records into master records. Preserve important information from all duplicates—last activity dates, deal associations, and custom property values. Create an audit trail showing which records were merged and why.
Step 3. Create a clean data management system.
Mark records to keep versus delete with a status column. Use the =HUBSPOT_LOOKUP formula to pull additional data for decision-making when duplicates have conflicting information. Handle edge cases that HubSpot’s dedupe tool typically misses, like similar but not identical company names.
Step 4. Execute bulk updates and deletions safely.
UPDATE master records with consolidated information first, then use DELETE actions for duplicate records. Process large datasets in batches using scheduled exports to avoid overwhelming your system. Maintain association data during consolidation to preserve relationship history.
Step 5. Implement advanced deduplication features.
Create fuzzy matching rules using spreadsheet functions to catch duplicates with slight variations in spelling or formatting. Set up ongoing deduplication by scheduling regular imports and applying your deduplication formulas to new contacts automatically.
Clean your database without the manual tedium
This systematic approach handles thousands of duplicates while preserving data integrity and creating a complete audit trail—capabilities that HubSpot’s native deduplication tools simply can’t provide. Your database will be cleaner and more reliable. Start deduplicating at scale today.
