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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’s native merge preview shows limited field comparisons and doesn’t provide comprehensive analysis of which populated fields will be overwritten with blanks. The preview interface only displays a subset of properties and doesn’t highlight data completeness issues.
You’ll discover how to create complete field comparison analysis and automated overwrite detection that shows exactly which data will be lost before you merge.
Build comprehensive merge validation with complete field analysis using Coefficient
Coefficient provides superior merge validation capabilities that go far beyond HubSpot’s limited merge preview interface.
How to make it work
Step 1. Import complete field comparisons.
Connect HubSpot to HubSpot through Coefficient and import both duplicate records with all properties selected. Create side-by-side comparisons in your spreadsheet that include all custom properties, integration fields, and system data. Use conditional formatting with rules like =AND(B2=””,C2<>“”) to highlight cells where the primary record has blank values that would overwrite populated data.
Step 2. Create automated overwrite detection.
Build formulas that automatically identify potential data loss scenarios. Use =IF(AND(ISBLANK(B2),NOT(ISBLANK(C2))),”WILL OVERWRITE: “&C2,”Safe”) to flag each field where valuable data would be lost. Create a summary formula like =COUNTIFS(D:D,”WILL OVERWRITE*”) to count total fields at risk for each merge operation.
Step 3. Develop merge impact scoring.
Create spreadsheet logic that calculates the potential data loss impact for each merge operation. Assign importance weights to different field types (contact info = 5, notes = 3, etc.) and multiply by the number of fields that would be overwritten. Use =SUMPRODUCT((D2:D50<>“Safe”)*importance_weights) to get a total risk score for each merge.
Step 4. Build dynamic merge recommendations.
Use Coefficient’s analysis capabilities to automatically recommend which record should be the primary merge target. Create formulas that compare data completeness: =IF(COUNTA(B2:B50)>COUNTA(C2:C50),”Use Record 1 as Primary”,”Use Record 2 as Primary”). This provides data-driven recommendations rather than relying on creation dates.
Step 5. Create bulk merge validation reports.
For multiple merge operations, create batch analysis reports that show potential overwrites across all planned merges. Use pivot tables or summary formulas to identify patterns in data loss risks and prioritize which merges need manual review before execution.
See exactly what you’ll lose before you merge
With comprehensive field comparison and automated overwrite detection, you can make informed merge decisions based on complete data visibility rather than HubSpot’s limited preview. These validation processes ensure you never lose valuable data unexpectedly. Start building your merge validation system today.
