Pomio CRM keeps imported contacts, companies, and deals next to the pipeline the team can see. A duplicate check before you write rows is how you protect history: one person, one company, one deal thread — not three parallel copies that nobody merges later.
What a duplicate check on import means
It is a deliberate match step before create: compare each incoming row to records already in the CRM, decide update-or-skip versus insert, and only then write. Match keys are usually email for people, website domain or legal name for companies, and a stable external identifier when you have one. Pair this with linking every CRM contact to a company so merged people still sit under one account.
Why skipping checks splits history
Blind insert creates parallel contacts and companies with partial notes, separate owners, and split deal trails. Reports double-count pipeline; handoffs miss context; cleanup becomes a project. That is the same hygiene failure as blank ownership — see why every CRM contact needs an owner — only now the mess arrives in bulk from a spreadsheet.
How to match: email, domain, and name rules
Prefer exact email (normalised to lower case) for contacts. For companies, prefer domain from the website or email, then normalised legal name. Use fuzzy name-only match as a review queue, not an automatic merge. When exporting for a round-trip, keep identifiers so re-import updates the same rows — CSV export of contacts and companies is the mirror of a careful import, not a reason to skip matching.
Exceptions that still need a rule
Brand-new lists with no overlap can still run the check and expect zero hits — that proves the rule, it does not waste time. Staging a file for review before write is fine; skipping the match step “because we are in a hurry” is not. If two real people share one mailbox, resolve ownership with a human decision, then document the rule — do not invent a second silent contact.
How Pomio CRM keeps duplicate hygiene visible
Imported records stay next to the pipeline the team can see. After each import, scan for near-duplicates, confirm owners on companies and contacts, and treat unexplained doubles as incomplete hygiene until merge or archive — the same visibility habit as other CRM fields the team relies on in reviews.
A practical import duplicate checklist
Before each import: normalise emails and domains in the file; choose match keys; run dry-match against live CRM; decide update, skip, or create per row; write only after review of collisions; assign owners on new companies and contacts; spot-check a sample in the pipeline view; schedule a short duplicate sweep after large imports — fix matches before debating campaign lists.
Go deeper
Is a unique email enough to prevent all duplicates?
No. People change jobs and mailboxes; companies change names and domains. Email is the strongest default for contacts, but company matching and periodic sweeps still matter. Pomio CRM keeps the resulting records visible so the team can catch what automation missed.
Should we auto-merge on every soft name match?
No. Soft matches belong in a review queue. Automatic merge on weak name similarity destroys history when two different buyers look alike. Prefer exact keys for auto-update; escalate fuzzy hits to a person.
Does Pomio CRM invent duplicates for us?
No. The product keeps imported records next to the shared pipeline. Your import process owns match rules and merge decisions; Pomio CRM makes parallel records easy to see and fix — it does not invent your data model.
How do duplicates relate to company ownership?
Parallel companies often appear when imports skip domain checks. Combine duplicate checks with an owner on every CRM company so merges have a clear accountable person and reporting stays honest.