Record Matching & Deduplication in Omatic Cloud
Compare data across your tech stack to spot and stop duplicate records — before they cause chaos.
What is Record Matching and Deduplication?
Record matching is Omatic Cloud’s process for comparing data in a source platform to data in a destination platform and identifying similar records between the two. By flagging similar data points, Omatic Cloud prevents duplicate records before they cause issues.
How It Works: Record Matching & Deduplication
Omatic Cloud puts you in the driver’s seat when it comes to sending data to your CRM.
Custom Search Criteria
Easily let Omatic Cloud know the criteria it should look for to deduplicate records. Simply set your custom search parameters to compare source data against destination data.
Needs Attention Feature
We’ll flag duplicate records — you decide what to do with them. Whenever you transfer data, Omatic Cloud automatically gathers potential duplicates for you to review.
Simplified Review Process
Omatic Cloud isolates potential duplicates, so you only need to review a handful of records among thousands. You decide to add, remove, edit, or merge them with existing CRM records.
How Duplicates Sneak into Your Systems
There’s a reason why nonprofits struggle with duplicate records. Complex tech stacks, name variations and changing biographical data can make it hard to know who’s who in your database.
Supporters with Engagements Across Your Tech Stack
If Jane is a donor in GoFundMe Pro, a volunteer in VolunteerHub, and a ticket holder in Eventbrite, it’s possible she will have three separate records when data transfers hit your CRM.
Supporters Who Use Nicknames Inconsistently
A donor may go by “James” in one giving form and “Jimmy” in another giving form, and now you have two records for the same person.
Supporters with Changing Addresses
Donors may change the mailing addresses, billing addresses, or email addresses over time — causing new duplicate records in your database.
Omatic Cloud can scan all your data sources against your CRM to spot duplicates or data errors that native import tools miss. Our integrations use ‘fuzzy’ data matching tools, so differences in names and addresses don’t produce new records.
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