Problem:
You have duplicate records where the same type of value could be stored in different fields.
For example:
Record A → Work Phone:
111-222-3333, Home Phone: (blank)Record B → Work Phone: (blank), Home Phone:
111-222-3333
By default, these two records will not be flagged as duplicates.
Solution: Use Group Name
The Group Name setting in Matching Models allows you to treat multiple fields as interchangeable. When fields share the same Group Name, DataGroomr compares values across those fields between records.
In other words, Group Name = “Phone” means:
Work Phone in Record A can match Home Phone in Record B.
Mobile Phone in Record A can match Work Phone in Record B.
Any phone field in one record can match any phone field in the other.
How to Configure It
Go to Setup → Matching Models.
Create or edit a Matching Model.
Add all the phone fields you want considered (Work, Home, Mobile, Other, Fax).
In the Group Name column, assign the same label to each (e.g.,
Phone).Choose Exact Match
Save the model and run analysis in Dedupe (Trimmr).
Result
In the Jon Smith example:
Record A: Work Phone =
111-222-3333Record B: Home Phone =
111-222-3333
Because both rules are grouped under Phone, the engine treats them as a match. These records will now appear in the same duplicate group.
Data Cleanup
Before comparison, all field values are automatically standardized:
Text fields → converted to lowercase and special characters removed
Phone numbers → digits only
Emails → converted to lowercase
Websites → normalized (protocol and leading
wwwremoved)
This ensures format differences do not block matches.
Best Practices
Use descriptive Group Names (e.g., “Phone,” “Email,” “Address”) so it’s clear which fields are interchangeable.
Don’t mix unrelated fields into the same group (e.g., Phone + Email) — this will cause false positives.
Review confidence scores — if one phone number should be enough to declare duplicates, ensure your threshold supports that.