Mass Merge


The Dedupe module includes the ability to mass merge duplicate groups based on match confidence level (the certainly that the matched records are duplicates).  All duplicate records are assigned a match confidence score of between 1-100. The higher the score, the higher the probability that the records within the groups are genuine duplicates. Match confidence displayed on the group is the average match confidence of the grouped records.


Tip: Review the records for each match confidence level before merging to ensure you make informed and accurate decisions.


To run a mass merge task, select the Mass Merge button from the duplicate group list view.

 

 

In the dialog window that appears:

  • Use the dual confidence slider to select a desired range (e.g., merge only groups between 80–95%).

  • Optionally, filter by Tags to include or exclude specific groups from the merge. Tags work together with the confidence range: they are only applied to groups that meet or exceed the confidence threshold.

  • Filter by Group size to target duplicate groups of a particular size (e.g., only groups of 2 records, or 10+ records). This allows you to focus on more manageable sets.

  • Filter by the Matched by model which matched the records together, if dataset is set up with multiple matching models


The mass-action dialog displays an estimated record count next to each filter, letting you preview how many records will be affected before proceeding.



 

Good to Know: Tags work in conjunction with the Match Confidence setting and will only be applied to groups with a match confidence above the set limit. You can also request AI recommendations in bulk. Mass AI Recommendations provide inline explanations and use colored tags to suggest whether to merge, unmatch, link, or split groups.



Mass-action dialog displays an estimated record count, so you can preview how many records will be affected before running the merge.


Finally, press the MERGE ALL button to begin merge.


Related topics:
Master record rules
Field value rules
Tags in DataGroomr App
Tags in DataGroomr Lightning Component
Merging Contacts with Multiple Account records



Mass Unmatch


The Mass Unmatch feature allows you to quickly separate records that were previously grouped together but should not be considered duplicates. This is especially useful when manual review or AI recommendations reveal false positives within matched groups.


To run a mass unmatch task, click Mass Unmatch from the duplicate group list view.


Use match confidence and the same filters that are available for the Mass Match to narrow down records that you are unmatching.


Tip: Mass Unmatch works particularly well in combination with AI recommendations and unmatch tags, allowing you to automatically identify and exclude records that the AI or your team has marked as not related.



After confirming your filters, click Unmatch All to separate the selected groups.


Good to Know: Unmatched records are immediately removed from their duplicate groups and will appear as individual or newly formed potential matches during the next deduplication scan. This helps refine your dataset and improve future match model performance.