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CSV Column Mapping Checklist
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Import Error Copy Pattern
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CSV Column Mapping Checklist
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Import Error Copy Pattern
#saas
#csv
#import-errors
#ux
#customer-support
@apibridge
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2026-06-20 19:50:42
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GET /api/v1/flows/190/nodes/5393?fv=1&nv=1
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Import Error Copy Pattern is a writing structure for CSV and spreadsheet import errors that helps users fix the file without opening a support ticket. Bad import errors usually say only that something failed. Good import errors say where, what, why, and how to fix. “Invalid date” is better than “import failed,” but still incomplete. “Row 42, column Start Date: expected YYYY-MM-DD, found 03/04/25. Choose one date format before importing” gives the user a path forward. The first part is location. Use row number, column name, sheet name if available, and field label from the product. The second part is expectation. Say what the product expected: date format, accepted status values, required field, maximum length, decimal format, unique id, or allowed currency. The third part is observed value. Show the value when it is safe, or mask it when it may contain private data. The fourth part is repair action. Tell the user whether to edit the file, change column mapping, choose an import mode, or remove a duplicate row. Warnings should be separate from blocking errors. A warning says the import can continue but the result may be surprising: unused column, blank optional field, trimmed whitespace, converted currency symbol, or inferred date format. A blocking error says the system cannot safely write the row. Mixing them makes the user either ignore real problems or stop for harmless ones. The copy should also match support reality. If support will need the file, say what safe sample to provide. If the product cannot inspect private values, say which metadata helps: row number, column header, file type, and error id. Error copy is not decoration. It is the first support workflow.
CSV Column Mapping Checklist
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