How to prevent duplicate records
Deduping is cleanup; prevention is what keeps you from doing it again. The cheapest duplicate is the one that never gets created.
Prevention means catching matches at every entry point - reps, imports, and forms - not just periodically merging the results.
Short answer
Prevent duplicate records by checking every new entry against existing data at the point of creation - in manual entry, imports, and form fills - and blocking or flagging matches before they save. Standardize values so matching works, use both exact and fuzzy rules, and route returning people to their existing record instead of a new one.
Step by step
Block on manual entry
When a rep creates a record, check it against existing ones and warn or block if it matches, offering the existing record instead.
De-dupe imports before load
Match incoming import rows against current records and against each other, so an import does not bulk-create duplicates.
Match form submissions
When a web form comes in, match it to an existing contact and update that record rather than creating a new one.
Standardize so matching works
Normalize company names, emails, and formats so the matcher can actually recognize duplicates that are spelled differently.
Every entry point needs a guard
Duplicates enter through three doors: manual entry, imports, and forms. Guarding only one leaves the others open. Prevention has to cover all three, and standardization underneath makes the matching reliable enough to trust with blocking.
How Ardovo helps
Ardovo checks every entry point - manual, import, and form - against existing records with exact and fuzzy matching, and routes returning people to their existing record. Rook does this automatically so duplicates are stopped at the door instead of merged after the fact.
Frequently asked questions
How do you stop duplicates before they are created?
Check each new record against existing data at the moment of entry and block or flag matches. Cover all three entry points - manual creation, imports, and web forms - since guarding only one leaves duplicates flowing in through the others.
Why do imports create so many duplicates?
Because a naive import loads every row as a new record without checking against what already exists or against other rows in the same file. De-duping the import against current data and within itself before loading prevents this.
Does duplicate prevention need clean data first?
They reinforce each other. Standardized values make matching reliable, and reliable matching makes prevention trustworthy enough to block on. Start standardization and prevention together so the matcher can actually recognize duplicates spelled differently.