HubSpotMatching existingcontacts with Excel data often creates duplicate records when email formats differ slightly or when the native matching logic fails to handle data conflicts properly.
Here’s how to implement advanced contact matching that significantly reduces duplicate creation and handles email variations effectively.
Use advanced matching to prevent duplicate contacts using Coefficient
Coefficientprovides sophisticated contact matching capabilities that address the common failures of HubSpot’s basic email matching system. The key is using UPDATE actions instead of INSERT to modify existing contacts rather than creating new ones.
HubSpotNativeimports often treat “john@company.com” and “John@company.com” as different contacts, leading to duplicates. Coefficient allows you to standardize email formatting in Excel before matching, while also providing selective property updates that preserve existing data.
How to make it work
Step 1. Standardize email formats in Excel before import.
Use Excel formulas like =LOWER(TRIM(A2)) to standardize email addresses by removing extra spaces and converting to lowercase. This prevents case sensitivity issues that cause duplicate creation.
Step 2. Set up Coefficient’s UPDATE export action.
Configure your import to use UPDATE instead of INSERT action. This ensures you’re modifying existing contacts rather than creating new records when email addresses match.
Step 3. Implement data validation before processing.
Create validation formulas in Excel to check email format consistency. Use functions like =IF(ISERROR(FIND(“@”,A2)),FALSE,TRUE) to identify valid email addresses before import.
Step 4. Use selective property updates.
Configure Coefficient’s data mapping to update only specific properties while preserving existing HubSpot data. This prevents the all-or-nothing overwrites that occur with native imports.
Step 5. Test matching logic with small batches.
Use Coefficient’s dynamic filtering to reference specific Excel cells containing test email addresses. Process small batches first to validate your matching logic before handling large datasets.
Eliminate duplicate creation with smart matching
Start usingAdvanced contact matching prevents the database bloat and data fragmentation that comes from duplicate records.these matching techniques to maintain clean contact data.