Data cleaning for CRM imports

Pipedrive import errors

Why Pipedrive skipped rows on import (and how to read the skip file)

Pipedrive imports the valid rows and writes the rest to a skip file, with a reason for each row. Most of those reasons are file problems you can fix before you re-import: a blank name, a currency symbol where a code is expected, a date it cannot read, or a non-numeric value in an ID column. Fix them once, re-import the skipped rows, and the skip file comes back short or empty.

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What the skip file says

The reasons above are the file-fixable ones. The skip file can also list rows skipped for reasons that are not about the file at all, which no amount of cleaning will change; see "What Sift can't fix" below.

Why it happens

• Blank names. A person or organization row with no name has nothing to key on, so Pipedrive reports "Name must be given" and skips it.
• Currency symbols instead of codes. A deal value written as a $ symbol is not a currency, so Pipedrive asks for a valid currency, a code like USD, rather than a symbol.
• Dates it cannot parse. An unparseable or ambiguous date (is 03/04 March 4 or April 3?) gets skipped as invalid rather than guessed at.
• Wrong type in an ID column. An ID column expects an integer, so a non-numeric value there triggers "ID must be an integer".
• Reasons that are not the file. Some rows are skipped for permission or plan limits, or a "not found" reference to a record that must already exist. Those are fixed in Pipedrive, not in the CSV.

The manual fix

1. Open the skip file Pipedrive gave you and read the reason next to each skipped row.
2. For "Name must be given", fill the blank name or organization fields.
3. For "Please provide valid currency", replace the currency symbol with a code like USD.
4. For invalid dates, standardize them to one clear, unambiguous format.
5. For "ID must be an integer", correct the ID values so the column holds whole numbers only.
6. Re-import only the skipped rows, so you don't duplicate the ones that already came through.

The Sift fix

1. Drop your CSV or Excel file into Sift. It runs in your browser; the file is never uploaded.
2. Sift fills or flags required name fields so no row lands with a blank one.
3. It strips currency symbols so amounts parse as numbers, and standardizes dates, previewing ambiguous rows so you decide the format, not the importer.
4. It checks number and integer types so ID columns hold what Pipedrive expects.
5. Run the readiness check against a mapped Pipedrive template and export a clean file, so the skip file comes back short or empty.

What Sift can't fix

Honesty matters here: some skip reasons are not about the file. If a row is skipped because of a permission or plan limit, or because of a "not found" reference to a record or user that must already exist in Pipedrive, no amount of cleaning the CSV will change that. Those are fixed inside Pipedrive, by adjusting access or your plan, or by creating the referenced record first, not in the file Sift touches.

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