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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 lacks native pre-merge validation capabilities to warn users about potential blank field overwrites. The platform’s merge preview shows field comparisons but doesn’t systematically flag data loss risks or provide automated validation rules.
You’ll learn how to build comprehensive pre-merge validation systems with automated overwrite detection, risk scoring, and systematic workflow checks that prevent data loss before it happens.
Build systematic pre-merge validation with automated risk detection using Coefficient
Coefficient enables comprehensive pre-merge validation through automated analysis and systematic checking that HubSpot’s native merge functionality cannot provide.
How to make it work
Step 1. Set up automated overwrite detection.
Import duplicate record pairs from HubSpot to HubSpot and create formulas that automatically identify fields where the primary record has blank values that would overwrite populated data. Use =IF(AND(ISBLANK(B2),NOT(ISBLANK(C2))),”RISK: Will overwrite ‘”&C2&”‘ with blank”,”Safe”) to flag each problematic field. Apply conditional formatting with red highlighting for cells containing “RISK” to make data loss threats immediately visible.
Step 2. Create merge risk scoring systems.
Build validation logic that calculates risk scores for each potential merge based on the amount and importance of data that would be lost. Create weighted scoring like =SUMPRODUCT((risk_flags=”RISK”)*(field_importance_weights)) where critical fields like email and phone get higher weights. Set up automated alerts using =IF(risk_score>threshold,”HIGH RISK – Manual review required”,”Proceed with caution”) to flag problematic merges.
Step 3. Implement systematic validation workflows.
Set up scheduled imports of your duplicate records with filtering to identify merge candidates, then run automated validation checks that flag problematic merges before they occur. Create a validation dashboard that shows =COUNTIF(validation_results,”HIGH RISK”) high-risk merges, =COUNTIF(validation_results,”MEDIUM RISK”) medium-risk merges, and =COUNTIF(validation_results,”Safe”) safe merges across your entire duplicate list.
Step 4. Build custom validation rules for business-critical fields.
Create spreadsheet-based validation that checks for specific fields that should never be overwritten with blanks. Use formulas like =IF(AND(ISBLANK(primary_email),NOT(ISBLANK(secondary_email))),”CRITICAL: Email will be lost”,”OK”) for essential contact information. Set up separate validation categories for different field types (contact info, deal data, custom properties) with appropriate risk levels.
Step 5. Create bulk validation reporting and alert automation.
For large-scale merge operations, create comprehensive validation reports that show potential data loss across all planned merges. Build summary reports using pivot tables or COUNTIFS formulas to identify patterns in data loss risks. Use Coefficient’s alert features to automatically notify team members when validation checks identify merges that exceed acceptable risk thresholds, enabling proactive review and correction.
Catch data loss before it happens
With systematic pre-merge validation and automated risk detection, you can identify and prevent blank field overwrites before they cause permanent data loss. These validation workflows provide the proactive protection that HubSpot’s reactive merge preview cannot deliver. Start building your validation system today.
