How to import a CSV into a CRM without creating duplicates

Duplicates are the reason most people dread moving CRMs. The same company turns up as “Acme Ltd.” and “ACME LIMITED”, a person has two email addresses, and a lead you gave up on comes back from the dead. Here is how to prepare a file, what a good import should catch, and how to check it before it changes anything.

Why duplicates happen

Names are typed differently. “Acme Ltd”, “Acme Limited” and “ACME, Ltd.” are one company to a human and three to a naive import.
Lists overlap. A list you bought, a list you built and a list exported from your old CRM all contain some of the same people.
Re-imports. You fix a column and import the file again, and everyone arrives twice.
Dead leads return. You archived someone for a reason, then a fresh list brought them back.

Step 1: split the file by business

If you run more than one business, do not import everything into one place and sort it out later. Split the CSV first, one file per business, and import each into its own workspace. It is far easier to separate rows in a spreadsheet than to untangle them afterwards.

Step 2: get the columns right

You do not need a perfect file, but a few columns do most of the work:

A name: full name, or first and last name.
A company, and ideally a website or an email, which tell a CRM which organisation someone belongs to.
A phone number if you will be calling.
Anything else you want to keep: job title, sector, location, LinkedIn, notes.

Delete columns you will never use before you start. FounderPipe guesses what each column means from its heading and lets you change the guess, and anything you leave as “ignore” is simply not imported.

Step 3: know what the matching looks at

A good importer compares rows with what you already have using more than an exact text match. FounderPipe compares:

Company names, ignoring case, punctuation, “&” against “and”, a leading “The”, and endings such as Ltd, Limited, LLP or PLC.
People’s names, ignoring titles like Mr, Dr or Prof.
Phone numbers, by their last ten digits, so “+44 (0)20…” and “020…” are the same number.
Website and email domains, which is how a person is tied to a company.

Matching is also careful where being generous would merge different things. An email address at a mailbox provider such as Gmail says who a person is, not where they work, and a link to a social-media page is not a company website, so neither is used to decide that two companies are the same.

This is rule-based matching, not magic. It will not know that “IBM” and “International Business Machines” are one company. That is why the next step matters.

Step 4: preview before anything is saved

The safest import is one you can read before it runs. In FounderPipe, after you map the columns, you see a plan showing how many rows are new and how many will be skipped, and why:

Already here: a match with someone you already track. Skipped.
Looks like someone already here: a likely match. Skipped, and listed so you can review it.
At an archived company: you gave up on that company, so the import leaves it alone.
Nothing to import: an empty or unusable row.

Skim the skipped list. If a row was skipped that you wanted, you can add it by hand. If rows you expected to be skipped are marked new, fix the file and run it again before you import.

Step 5: import, and keep the receipt

Skipped rows are skipped, not merged: an import never changes a person or company you already have. Every file you import is kept as a batch, with its source file name and time, and you can open a batch to see only what came in with it. That makes a bad import easy to spot.

Because an import does not overwrite existing records, running the same file twice does not create copies: the second time, the plan should show those rows as “already here”.

Try an import, no card

A short checklist

Export from your old tool as CSV, or tidy your spreadsheet.
Split by business and delete columns you will not use.
Make sure each person has a name, and a company plus a website or email where you have them.
Check the column mapping, then read the plan and the skipped list.
Import, then open the batch to confirm it looks right.

Running more than one business? See how workspaces keep each one’s contacts apart, or how to choose a CRM for multiple businesses.

Questions about importing a CSV into a CRM

How do I import a CSV into a CRM without duplicates?

Clean and split your file first, map the columns, and use a CRM that matches rows against existing records and shows you a plan before saving. FounderPipe matches on company name, person name, phone number and website or email domain, and skips matches instead of creating copies.

What does FounderPipe do with rows that already exist?

It skips them. An import never changes a person or company you already track, and the plan lists what will be skipped and why before anything is saved.

Will an import bring back a lead I archived?

No. Rows at companies you have archived are left out, so a fresh list cannot resurrect a lead you gave up on.

Does it catch every duplicate?

No. Matching is rule-based: it handles differences in case, punctuation, legal endings, titles, phone formatting and domains, but it cannot know that two very different names are one company. Skim the skipped list and the new rows before you import.

Can I import into more than one business?

Yes. Each business has its own workspace, so split your file and import each part into the right one. See how workspaces work.

Can I import a file exported from another CRM?

Any CSV works. FounderPipe guesses what each column means from its heading and lets you change the guess before importing.

Test it on your messiest list

Import a CSV you know has duplicates and see what gets matched.

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