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Candidates and imports

A candidate import has skipped or failed rows

Use column mapping and row-level results to separate successful records from duplicate, invalid, or failed entries.

Everyday work3 min readCandidates

Before you begin

Create candidate access; bulk resume import also requires Upload resume access. · The original file and access to its import review or result.

Work through this checklist

1. Identify the import path

This checklist focuses on CSV and XLSX imports. Resume uploads use a separate review queue; a resume waiting for review is not the same as a completed candidate record.

2. Inspect the preview

Review the ready, duplicate, and invalid counts. Read the messages beside the affected rows. If no importable rows appear, check both the displayed error and the column mapping.

3. Correct column mapping

Use Review column mapping to check where each source column goes, then select Apply mapping. Map only one source column to each destination field. Review the updated preview before committing.

4. Investigate duplicates

An existing candidate or an earlier row with the same email or phone can be marked as a duplicate. Check the existing record rather than altering contact information to force a second record through.

5. Review what was actually saved

Read the final row outcomes, not just the upload progress. Successful rows can be kept even when other rows fail. If a message says a candidate was created but a related import step needs repair, inspect that candidate and the original import before retrying.

If you still need help

If the exact file was already uploaded, open that import. Do not assume every row failed or upload the same whole batch repeatedly. Escalate unresolved row errors with the import name and error text, excluding candidate details from the initial report.

Read the complete product guide

Reconcile the batch before retrying

Keep the original file and note which rows were ready, duplicated, invalid, or created. Compare the final outcome with the preview. A batch can contain successful records alongside unresolved rows, so the recovery task is to identify the remaining work accurately.

For a duplicate, compare the existing candidate using authorized identifying information. For an invalid value, correct the source or mapping that caused the problem. Do not change a real email address or phone number simply to avoid duplicate detection. If the underlying identity remains uncertain, ask the record owner to review it.

Check a sample of successful records

Open created candidates and confirm names, contact details, and recruiting fields against the source. A successful row can still contain an incorrect mapping. Resolve that issue before importing a larger batch. Report the import reference, affected outcome category, and redacted row error when requesting help. Share the source file only through the agreed process if support needs it.

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