How to identify duplicate contacts without merging different people
A contact deduplication review helps locate repeated records while preserving important identity differences. It is useful before importing or cleaning a list when the matching rules are explicit.
Start with the right material.
- What you provide
- a small visible contact table.
- The intended result
- Create a cleaned CSV using the user's duplicate key and preserve a duplicate-review report.
How the workflow works.
Choose the identifiers that support a match and explain any normalization. Keep candidate groups with their original row references so conflicting names, addresses or roles can be inspected.
What to check in the result.
Confirm uncertain groups before deleting or merging records. Shared names, household numbers and general business email addresses can belong to different people or legitimate separate entries.
Import the CSV with a consistent delimiter and inspect text identifiers, dates and amounts before using spreadsheet totals. Keep the original file available while checking any automatic type conversion.
Learn from the worked example.
The downloadable CSV example uses these columns: Email, Names seen, Notes retained, Source rows, Review status. Compare a complete record with the source before sorting, combining or importing your own output.
The supplied example is illustrative. It is not a recorded run on your data.
Download the example ↓Use it with your own material.
- Open the source you want to work with and activate WebAct on that tab.
- Copy the task from the hero, add any required fields or preferences, and review the proposed actions.
- Compare the first result with your source. Ask for a specific correction or refinement where needed.