Find and Merge Duplicate Contacts
Learn how to use ContactConverter's intelligent deduplicator to find and merge duplicate contacts automatically while preserving important information.
How Duplicate Detection Works
ContactConverter uses advanced fuzzy matching algorithms to identify potential duplicates by comparing multiple contact fields and calculating similarity scores.
Step-by-Step Process
Import Your Contacts
Upload your contact file to the ContactConverter deduplicator.
Start by importing your VCF or CSV file into the deduplicator tool. The system will analyze all contacts for potential duplicates.
Configure Detection Settings
Adjust the similarity threshold for duplicate detection.
Set how strict the matching should be. Higher values (80-90%) find only very similar contacts, while lower values (50-70%) catch more potential duplicates.
Run Duplicate Analysis
Let the system scan for duplicate contacts.
The fuzzy matching algorithm compares names, phone numbers, and email addresses to identify potential duplicates.
Review Duplicate Groups
Examine each group of potential duplicates.
Review the suggested merges carefully. The system shows similarity scores and highlights matching fields.
Merge or Skip
Choose to merge contacts or skip if they're not duplicates.
You can merge individual groups, merge all at once, or skip groups that aren't actually duplicates.
Matching Criteria
Understanding how the system identifies potential duplicates
Names
Compares first and last names using fuzzy matching
Phone Numbers
Matches phone numbers regardless of formatting
Email Addresses
Exact match on email addresses (case insensitive)
Organization
Compares company or organization names
Common Duplicate Scenarios
How to handle different types of potential duplicates
Same person, different phone numbers
Example: John Smith with work phone vs. John Smith with mobile phone
Recommended action: Merge and keep both phone numbers
Nickname vs. full name
Example: Bob Johnson vs. Robert Johnson
Recommended action: Merge and use the full name
Old vs. new email address
Example: Same person with old work email and new personal email
Recommended action: Merge and keep the current email
Different people, same name
Example: Two different John Smiths
Recommended action: Skip merging, keep as separate contacts
Pro Tips
- Start with a high similarity threshold (80%+) to catch obvious duplicates
- Review each merge suggestion carefully before confirming
- Keep the most complete contact when merging
- Back up your contacts before running the deduplicator
- Run the tool multiple times with different thresholds if needed
Ready to Find Duplicates?
Use ContactConverter's deduplicator tool to clean up your contact database.