Bulk Merge
Bulk merge is a way to merge many duplicate sets in a CRM in one action, with the same primary record and merge rules applied to each set. It's how teams bulk merge duplicates once a search has found more sets than anyone could merge one by one, whether those are contacts, companies, accounts or leads.
A bulk merge is a one-off action: someone selects the sets, starts the merge and checks the results. That sets it apart from scheduled automatic merging, which runs on its own as new duplicates appear. Because one action changes many records, the rules matter more than they do in a single merge. A rule that picks the wrong surviving record, or the wrong value in a field, repeats that mistake in each set, so the rules are previewed first and uncertain sets are held back for a person to check.
See how Dedupely merges duplicates in bulk in your CRM
What Is Bulk Merge?
Bulk merge, also called mass merge, is the large-scale form of merging duplicate records. Instead of opening each duplicate set, choosing the surviving record and merging, a team selects many sets at once and merges them under one set of rules. It works on the same objects as any merge: contacts, companies and deals in HubSpot; accounts, contacts and leads in Salesforce; people and organizations in Pipedrive; leads in Close; and contacts in Nimble and Google Contacts.
Take a search that matches contacts on exact email and finds 400 duplicate sets, one of them "J. Smith" and "Jon Smith," both at jon@acme.com. Merged one by one, that's 400 separate merges, each with its own chance of a different choice. In a bulk merge, all 400 sets are merged in one action with the same rules, for example the oldest record survives and the filled phone number wins over a blank one.
Tools differ in how the sets are chosen. Hand-picked selection merges the sets a person ticks, which gives close control over each batch. Page-level selection merges a screen of results at a time, which keeps batches small enough to check. Selecting all the results of a search merges the whole list at once, which is the fastest way to clear a backlog of clear matches. Many teams use all three: everything at once for their strictest search, smaller batches for looser ones.
How Bulk Merge Works
A bulk merge follows the same decisions as a single merge, but each decision is made once, before the batch starts, and then applied to many sets:
- Find the sets. A duplicate search groups matching records into duplicate sets. The stricter the search, the more of its sets are safe to merge without opening each one.
- Set the rules. The rule for the surviving record and the rule for each field are set before anything is selected, because they apply to each set in the batch. Without custom rules, a tool may fall back on the CRM's own merge logic.
- Hold back the risky sets. Sets with an unusual number of records, placeholder values such as "N/A" or very short values are often set aside for review, so they don't ride along with the clear ones.
- Preview a few results. Checking the merged result for a handful of sets shows whether the rules keep the values you expect.
- Select and merge. The sets are selected by hand, by page or as a whole result list, and the merge starts. In many tools a large batch works through the sets one after another, so stopping it partway leaves the finished merges as they are.
- Check the CRM. A look at a sample of merged records confirms that values, activity and associations ended up where they should.
Why Bulk Merge Matters for CRM Teams
A large backlog of duplicates stays in the CRM until someone merges it, and while it's there it keeps doing damage. Contact and account counts stay inflated, pipeline reports count the same customer more than once, activity history stays split across records, and two reps can work the same lead. In CRMs that bill by contact or record count, each extra record also adds to the bill. Merging set by set clears that backlog slowly, so those effects last longer than they need to. Teams that bulk merge duplicates clear it in far fewer actions.
Bulk merging also makes the results consistent. When hundreds of sets are merged by hand, different people make different choices about which record survives and which value wins, and the CRM ends up with several versions of "clean." One set of rules applied to the whole batch gives each merged record the same logic, which makes the data easier to trust and to explain.
The same scale works against a bad rule. A rule that keeps an outdated email, or a search that groups different people, repeats its error in each set it touches, and in many systems a merge is hard or impossible to reverse. That's why the checks before a bulk merge, such as previews, held-back sets and a small first batch, matter as much as the speed.
Getting Started With Bulk Merge
Start with the search you trust most, such as an exact match on email or a customer ID, and set the rules before you select anything. Decide which record survives and which value each field keeps, and check the fields that are often blank or out of date on one of the records.
Preview the merged result for a few sets, then merge a small first batch and look at those records in the CRM. When the values, activity and associations look right, merge the rest of that search's results. Looser searches come next, in smaller batches, with more sets opened and checked along the way.
Keep the risky sets out of the batch. Large sets, sets built on placeholder data and sets that don't look right are better merged by hand, rejected or sent to a person for review. Keep a record of what each merge changed, so a mistake can be traced and the original values put back.
In Dedupely, Bulk Merge carries out this approach: you select several sets, a whole page or "Select all X matches," and the Primary Record and Merge Rules you've set apply to each one, with a preview before anything changes in the CRM. Safety Settings keep risky matches out of bulk selection by moving them to the Excluded tab, where they can be merged by hand, rejected or sent to Manual Review.
Key Takeaways: Bulk Merge
Bulk merge is merging many duplicate sets in one action, with the same rules for the surviving record and each field's value applied to all of them. It clears a large backlog faster than merging set by set and gives each merged record the same logic, but a bad rule repeats in each set, so the rules are previewed, a small batch goes first and risky sets are held back. In Dedupely, Bulk Merge merges several sets, a whole page or "Select all X matches," using the Primary Record and Merge Rules you've set. Safety Settings keep risky matches out of bulk selection, sets in Manual Review are left out, "Cancel all" stops a running bulk merge, and Merge History records the original records of each merge. For new duplicates on a schedule, there's Auto Match and Auto Merge.
Frequently Asked Questions About Bulk Merge
How do you bulk merge duplicates in a CRM such as Salesforce or HubSpot?
To bulk merge duplicates, run a duplicate search, set the rules for the surviving record and each field, preview a few results and then merge the selected sets in one action. The steps are the same in Salesforce, HubSpot, Pipedrive or Close, and for contacts, companies or deals. Built-in merge tools often handle a few records at a time, so a large backlog often calls for a tool that merges many sets at once. Start with your strictest search, merge a small batch, check those records in the CRM and then merge the rest. In Dedupely, Bulk Merge lets you select several sets, a whole page or "Select all X matches" in a Duplicate Search, and the Primary Record and Merge Rules you've set apply to each one. Without Merge Rules, Dedupely follows the CRM's own merge logic. The in-line preview and the Preview Merge panel show the result before anything changes.
Why do native CRM merge tools only merge a few records at once?
Native merge tools are built around one person comparing a few records side by side and choosing what to keep, so many of them limit how many records go into one merge. Salesforce's native merge stops at three records, Pipedrive merges duplicates one by one, and Nimble's native merge takes two to five contacts. That works for the occasional duplicate a rep notices. It doesn't scale to a cleanup that finds hundreds of sets, because each set becomes its own merge, with its own choices and its own chance of a mistake. A dedicated tool handles the scale by applying saved rules to many sets at once instead of asking for a decision on each. In Dedupely, Bulk Merge merges several sets, a page or all the matches in a Duplicate Search in one action, and in Salesforce it can merge thousands of records that way. In Nimble, Dedupely merges all the records in a match at once.
What is the difference between bulk merge and auto merge?
A bulk merge is a one-off action you start by hand, while auto merge runs on a schedule and merges new duplicates as they appear. Bulk merging suits a cleanup: you choose the sets, merge them and check the results. Automatic merging suits ongoing upkeep once a search has proven reliable, because no one selects the sets each time. Both use the same rules for the surviving record and each field. In Dedupely, Bulk Merge merges the sets you select. Auto Merge belongs to one Duplicate Search and runs as soon as possible, every set number of minutes, hours, days, weeks or months, on chosen days or between chosen hours. Before turning it on, you confirm the search, matching, filters and schedule, and that it merges all current and future duplicates matching the search. It skips Excluded matches and sets in Manual Review, and sends low-confidence matches to Manual Review instead of merging them.
How do you bulk merge without merging the wrong records?
Check the search, the rules and the riskiest sets before you merge. Start with a strict search on a strong field such as email, open a sample of its sets and make sure each one describes one person or company. Then confirm which record survives, which value wins in each field, and that a filled value keeps winning over a blank. Hold back sets with many records, placeholder values such as "N/A" or very short values, and merge a small batch first. In Dedupely, Safety Settings exclude risky matches from bulk selection: by default, matches with more than 20 records and matches built on poor or example data, such as John Doe, go to the Excluded tab, and a very short values rule can be turned on. Blank values never win a merge, and Merge Rules can make placeholders lose. Rejected Matches keeps false pairs out of future results.
Can a bulk merge be undone?
Often not, since a merge is hard or impossible to reverse in many systems. In Dedupely, because of how two-way CRM syncing works, merges can't be undone, and that includes each merge in a bulk merge. Some CRMs keep removed records for a while, such as Salesforce's Recycle Bin for 15 days, but the surviving record has already changed, so restoring the original state often means rebuilding it. The protection has to come before the merge: previews, held-back sets and a small first batch. If a bulk merge is running and something looks wrong, "Cancel all" stops it, and the merges already finished stay as they are. Merge History shows each merge with its date and every original record and its values, links to the record in the CRM, and downloads as a CSV. With that file, you can restore the original values by hand or recreate the records and merge them again with corrected Merge Rules. Who ran the merge is in the Audit Log, which only admins can see.
