Each guide covers a different part of that job. The process article shows how to match source headers to a destination template and validate the file before you import. The QuickBooks article explains how to prepare a CSV for the import format you actually use, starting from the sample in your own company. The HubSpot article maps a contacts export to HubSpot property headers and checks the blanks HubSpot ignores. The Shopify article maps a customer export to Shopify's customer CSV columns and checks the yes/no and address-code values. The dates and zeros article keeps calendar values unambiguous and preserves leading zeros in IDs, postal codes, and references. Map the file on the home page in your browser. Preview the first ten rows free, then pay $29 once for the complete mapped CSV. There is no subscription or account.
Guide library
CSV mapping guides
A small library for remapping exports to the columns an accounting, CRM, or payroll import actually expects.
Remap CSV columns for import
A reviewable sequence for matching source headers to a destination template, checking sample rows, and validating the file before import.
Prepare a CSV for QuickBooks import format
Start from the sample in your own QuickBooks import screen, map columns carefully, and test a small batch before the full load.
Import contacts into HubSpot from a CSV
HubSpot's file rules for contacts, the property names to use as target headers, and a worked signup-list example with the blanks and phone formats to check.
Import customers into Shopify from a CSV
Shopify's customer CSV rules, the column names to use as target headers, and a worked store-export example with the yes/no and address-code columns to check.
Keep CSV dates clear and leading zeros intact
Treat IDs as text, keep leading zeros, and use unambiguous dates so spreadsheets and importers do not rewrite the values.
Sample files
Each worked example uses small CSVs you can download. They're synthetic: made up for these guides, not from a real company, customer or bank. Open the free preview, drop the source file on Input A, paste the target header row into Input B, and check the mapping before you try your own export.
Column mapping
- source-export-sample.csv has 5 invoice rows in 7 columns. destination-template-headers.csv is the 6-column header row the import expects. All six targets auto-map, but Inv # shows only a 20% match, so check it. One row is flagged because it has no email. Walkthrough: column mapping worked example.
QuickBooks bank upload
- Three columns: bank-export-signed-amount-sample.csv has 6 rows with money out already negative. Target
Date,Description,Amountand pick Payee / Memo for Description yourself. Compare your result with quickbooks-bank-3-column-after-sample.csv. - Four columns: bank-export-money-in-out-sample.csv has 6 rows with separate Money Out and Money In columns. Target
Date,Description,Credit,Debit, pick Transaction Details, then Money Out for Credit and Money In for Debit. All six rows get flagged for a blank Credit or Debit cell, which is correct for this layout. Compare with quickbooks-bank-4-column-after-sample.csv.
Walkthrough: QuickBooks bank CSV worked example.
HubSpot contacts
- contacts-export-sample.csv has 5 event-signup contacts in 8 columns. hubspot-contacts-headers.csv holds 7 HubSpot property names. Pick Organization for Company name and ZIP for Postal code. Two rows are flagged for blank cells. Walkthrough: HubSpot worked example.
Shopify customers
- customers-export-sample.csv has 5 store customers in 13 columns. shopify-customers-headers.csv holds 12 Shopify customer CSV column names. Pick state for Default Address Province Code and postcode for Default Address Zip. Two rows are flagged for blank cells. Walkthrough: Shopify worked example.