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Import multiple candidates from a CSV file. You choose the destination (teamspace, client, job), map your CSV columns to Lope fields, run a health check, and import.

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Supported CSV format

  • File type: .csv only
  • File size: Max 25 MB
  • Encoding: UTF-8 recommended
  • First row: Used as headers (column names)

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Import flow

  1. Go to the candidates view
  2. Click Import -> Import CSV
  3. Upload your CSV file
  4. Choose Location - Select teamspace, client, and optionally job. This sets where all imported candidates go.
  5. Click Map CSV headers
  6. Map columns - For each CSV column, choose a Lope field (or “Don’t include” to skip)
  7. Click Run health check - Validates emails, dates, and flags issues
  8. Fix issues (optional) - Use the Edit tab to correct faulty cells
  9. Click Import CSV

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Destination vs. column mapping

Destination is set by the Location picker (teamspace -> client -> job). All imported candidates go there. You do not map CSV columns to set the destination when you’ve selected a client and job.
  • If you select a client - The “Client” mapping option is hidden. All candidates go to that client.
  • If you select a job - The “Job” mapping option is hidden. All candidates go to that job.
  • If you select a client but no job - You can map a CSV column to Job. Lope creates jobs for any job titles in the CSV that don’t exist and assigns candidates to them.
  • If you select no client - You can map a CSV column to Client (client name). Candidates are imported without a client unless you select one in the Location picker.

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Standard built-in fields

These are the built-in Lope fields you can map CSV columns to:
Mapping labelFieldDescription
NamenameCandidate full name
EmailemailEmail address (validated in health check)
LinkedinlinkedinLinkedIn profile URL (normalized on import)
GithubgithubGitHub profile URL (normalized on import)
Clientproject_nameClient name, only shown when you haven’t selected a client in Location
Jobjob_titleJob title, only shown when you haven’t selected a job. If client is selected, Lope creates missing jobs and assigns candidates.
CVpdf_storage_urlURL to CV/resume file
StagestagePipeline stage (see stage values below)
NotescommentsNotes or comments
Stage values - You can use numbers (0-6) or text. Lope normalizes common synonyms:
ValueMaps to
0, “sourced”, “source”, “prospect”, “new”, “applied”Sourced
1, “interview”, “screen”, “phone screen”, “onsite”Interviewed
2, “not a fit”, “rejected”, “declined”, “disqualified”Not a fit
3, “unassigned”, “unknown”, “n/a”Unassigned
4, “screened”, “screening”Screened
5, “review”, “reviewed”, “assessment”Reviewed
6, “placed”, “hired”, “offer accepted”Placed

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Custom columns

Custom columns are workspace-level fields you create (e.g. “Phone”, “Salary expectations”, “Skills”). You can map CSV columns to existing custom fields or create new ones during import.

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Mapping to existing custom fields

If your workspace has custom fields, they appear under Custom in the column mapping dropdown. Map a CSV column to Custom: <field name> to import into that field.

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Creating new custom columns during import

  1. For a CSV column, open the Column Type dropdown
  2. Click Create new column
  3. Enter a Column name (e.g. “Phone”, “Portfolio URL”)
  4. Choose a Column type (see types below)
  5. Click Create & Map
The new field is created when you complete the import. It appears as a pending field “(new)” until then.

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Custom column types

TypeUse forExample CSV values
TextShort or long text”Senior Engineer”, “Berlin”
NumberNumeric values”5”, “120000”, “3.5”
DateDates (ISO, dd/mm/yyyy, Excel serial, etc.)“2025-01-15”, “11-Sep-2025”
URLWeb links”https://portfolio.com”
PhonePhone numbers”+1 555-123-4567”
CheckboxBoolean (yes/no, true/false, 1/0)“yes”, “true”, “1”
SelectSingle choice from options”Remote” (options created if new)
Multi-selectMultiple values, separated by semicolon, pipe, or comma”Python;Java;React”
Multi-select and Select - Values are matched to existing options by label. If a value doesn’t match, a new option is created automatically.

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Don’t include

Map a column to Don’t include to skip it. The column is not imported. Use this for columns you don’t need (e.g. internal IDs, duplicate data).

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Auto-suggestions

When you upload a CSV, Lope suggests mappings based on:
  • Header names - Synonyms like “full name” -> Name, “e-mail” -> Email, “linkedin url” -> Linkedin, “client” -> Client, “notes” -> Notes
  • Email detection - If no column is named “email” but values look like emails, that column may be suggested for Email
You can change any suggestion before importing.

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Health check

Before importing, run the health check. It validates:
  • Invalid emails - Flags rows where the email doesn’t look valid
  • Date format - Warns if dates may not parse correctly
  • Phone format - Checks phone-like values
  • Empty or problematic cells - Highlights issues
Use the Edit tab to fix faulty cells, then re-run the health check.

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Row filtering

Rows where both name and email are empty are skipped and not imported.