Overview
Duplicate checks in SalesExec help prevent identical or highly similar leads from being entered into your system multiple times. This improves data quality, prevents sales users from working the same lead twice, and reduces confusion across teams. A duplicate check rule evaluates incoming leads against existing records using one or more matching criteria.
When a new lead matches the conditions of a duplicate rule, SalesExec identifies it as a duplicate and blocks insertion or handles it based on your configuration.
Key Functionality
Define duplicate check sets comprised of one or more fields.
Evaluate incoming leads against existing records to detect duplicates.
Use and/or logic across fields and sets to fine-tune how duplicates are identified.
Set a lookback period to limit the system's search for duplicates to a specific timeframe.
Ensure clean lead data and minimize redundant workload for sales teams.
How to Use This Feature
In SalesExec, go to More > Settings > Lead Fields to access lead configuration.
Click Edit for the Record Type you want to add a duplicate check to (you may only have one record type available).
Click the Duplicate Checks tab.
Click Add Duplicate Set to add a new set of duplicate check rules.
Click Add Field to define a data field that the system will check on to determine if a lead is a duplicate. Select a field from the dropdown list
The Lookback (hours) field defaults to 720 hours (30 days), but you can change this to meet your business standard.
Pro Tip: Multiple lead fields in a single duplicate set will be evaluated with an "and" statement, meaning both fields will need to match with data from an existing record for the new lead to be identified as a duplicate.
On the other hand, multiple duplicate sets will be evaluated with an "or" statement, meaning that if the criteria from either duplicate set results in a match a record will be identified as a duplicate.
Additionally, the duplicate check evaluates exact matches. Blank space, special characters, and upper and lower case characters are a factor in duplicate check matching.
Best Practices
Use the most unique and reliable fields available in your data (such as email address or phone number) as the basis of duplicate detection.
Combine fields into a single set when matching on exact combinations is critical. For example, requiring exact match on first name and email prevents false positives.
Create multiple sets when you want different matching rules. For example, one set matching email alone and another matching phone number alone.
Set the lookback period to a timeframe that makes sense for your lead volume and lifecycle; shorter windows reduce processing overhead, longer windows catch more duplicates.
Regularly review and refine duplicate check sets based on real-world duplicate patterns.
Troubleshooting
If duplicates are still being created, verify that your match criteria align with how lead data is formatted. Exact matches are required, including case, spacing, and special characters.
If you see too many false positives, consider loosening criteria or separating fields into multiple sets to adjust matching logic.
Ensure the duplicate check configuration is active for the correct record type — duplicate rules apply only within the record type where they are defined.
If leads are imported from external sources, confirm that formatting (such as phone formatting or email case) is consistent with the fields used in the duplicate check.
Remember that blank values and special characters impact exact matching, so ensure data quality before matching.