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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.”
When HubSpot exports separate deal and customer data without common identifiers, you’re left with valuable datasets that can’t be meaningfully connected for analysis or reporting.
Here’s how to merge these separate exports using advanced matching techniques and data enrichment to create unified datasets.
Prevent merging issues with association-preserved imports using Coefficient
Coefficient eliminates the need for post-export merging by pulling unified data from HubSpot that includes proper identifiers from the start, but also provides powerful tools for working with existing separated exports.
How to make it work
Step 1. Import deals with associated contact IDs.
Use Coefficient to pull deals with associated contact IDs automatically included, company associations for additional matching opportunities, and contact emails in deal imports for alternative matching keys. This prevents the identifier problem entirely.
Step 2. Apply fuzzy matching for existing separate exports.
When working with already-separated data, bring both datasets into a single spreadsheet and create matching algorithms using company name variations with SEARCH or FIND functions, phone number matching, and email domain matching for B2B scenarios.
Step 3. Build multi-criteria matching formulas.
Create formulas that attempt matching on multiple fields: primary matching on company name + contact last name, secondary matching on email domain + deal source, and tertiary matching on phone area code + industry for comprehensive coverage.
Step 4. Enrich data with additional HubSpot fields.
Use Coefficient to pull additional HubSpot data that might provide missing linking fields, such as recent activity associations, form submission data, and campaign attribution data that can serve as alternative matching criteria.
Achieve higher match rates with comprehensive data
This approach significantly improves match rates compared to manual spreadsheet manipulation alone, giving you unified datasets that preserve valuable relationships between deals and customers. Start creating better data connections today.
