Use filters to control which records are scanned and shown, helping you target specific segments and reduce false positives during matching.
Filters are a powerful way to narrow down and control how duplicates are identified and displayed in Dedupely. Whether you’re managing a post-import cleanup, working within specific pipelines, or focusing on record ownership, filters give you the precision to streamline your deduplication process safely and efficiently.
Why use filters?
Filters help you:
- Target duplicates by specific owners, regions, or pipeline stages.
- Clean up recent imports or migration batches by filtering based on create dates.
- Focus deduplication on a specific segment of your CRM data.
- Refine search results to reduce false positives and increase match accuracy.
Filtering by native and custom fields
Dedupely supports filtering across:
- Native fields (e.g., Email, Owner, Lifecycle Stage, Pipeline, Create Date).
- Custom fields unique to your CRM setup.
This gives you full flexibility to tailor your deduplication based on your business-specific data structures.
Types of filters in Dedupely
Dedupely provides two distinct filtering options within your Search Pads. Knowing when and how to use each will help you get better results and safer merges.
1. Filter records to be matched (Add filter)
This is the first filtering option you’ll encounter when creating or editing a Search Pad. It controls which records are eligible to be matched in the first place.
Example:
You only want to match Contacts where the City = Detroit. This filter ensures that Dedupely only scans Detroit-based records for duplicates.
This filter restricts the input pool of records being analyzed for matching.
2. Filter Records Within Each Match Group
Once matches are found, these filters let you determine which match groups are shown based on the data inside them.
You’ll find these under the “Filter Matches” section and can choose from:
- Only one record in match passes: At least one record in the match group must meet the condition.
Example: Match on Name + Email, but only show matches where one record has City = Detroit.
- All records in match pass: All records in the match group must meet the condition.
Example: Only show matches where every record has Lifecycle Stage = Customer.
- Following fields are unique across all records in a match: Only show match groups where a specific field has different values across all records.
Example: All records in the group have unique Phone Numbers.
These options let you fine-tune which matches are worth reviewing or merging, especially when working with large datasets.
How to apply Filters
- Navigate to a Search Pad or create a new one.
- Under Add Filter, apply your first filter to restrict which records are scanned.
- Optionally go to Filter Matches to control which match groups appear.
- Use AND/OR logic to combine multiple filters:
- AND: All conditions must be true.
- OR: At least one condition must be true.
You can mix and match both types of filters for highly customized duplicate searches.
Filter use cases by CRM
- HubSpot: Filter by Lifecycle Stage, Contact Owner, or Email Subscription Status.
- Salesforce: Filter by Record Type, Lead Status, or custom geographic fields.
- Pipedrive: Narrow matches by Pipeline, Deal Stage, or custom tags.
What happens after filtering?
Once your filters are in place:
- Search results will update based on your conditions.
- You can run a scan to identify duplicates only within the filtered dataset.
- You can then merge results using Single, Bulk, or Auto Merge.
To learn more about merging, visit:
Need help?
Not sure how to set up your filters? Reach out to our team for unlimited support via email, chat, or Zoom. We’ll help you structure your searches to match your goals.