Skip to main content
The import wizard lets you bulk add people to Spott, for example when migrating from another system or uploading a sourcing list. Each row in your file becomes one person. You can import up to 1,000 records per import, from CSV or Excel (.xlsx) files.

​
What you can import

When you upload a file, you choose what the rows represent:
Yes, you can import contacts too. The wizard is not candidate-only. Pick Contacts to bulk-load client contacts, or Any if your file mixes candidates, contacts, and companies.
Companies do not need their own file. Whenever a row has a company on it, Spott matches it to an existing company or creates a new company record, and links the person to it. Under Actions you can also Add to list or Add to job, which applies to every record in the import.
The import wizard upload step, with the Candidates, Contacts, and Any options

​
Start an import

1

Open the Candidates page

Navigate to Candidates from the main sidebar.
2

Open Import / Export

In the top right corner, click Import / Export, then select Import from CSV. This opens the import wizard. Admins can also reach it from Settings > Import.
3

Upload your file and pick a type

Select the CSV or Excel file from your computer, choose Candidates, Contacts, or Any, optionally add a List or Job, then click Start Import. Spott analyzes the file and prepares the mapping.
The Import / Export menu on the Candidates page

​
Map columns to Spott fields

Spott reads your column names and sample data and suggests a mapping for each column automatically. Your headers do not have to match Spott’s field names: “Job Title” is recognized as Work Experience Title, “City” as Location. Review the suggestions and adjust where needed. For each column you can:
  • Accept the suggested Spott field
  • Pick a different Spott field from the dropdown (use the search box at the top)
  • Skip the column so it is not imported
Skipped and unmapped columns are ignored. Nothing else in the file is imported, so a column only lands in Spott if it is mapped to one of the fields below.
The column mapping step with AI-suggested mappings

​
Fields you can map to

These are the Spott fields available in the mapping dropdown. The list is complete: if a column has no matching field below, it cannot be imported.
The Spott Field dropdown with the list of available fields
There is no Full Name field: split names into a First Name and a Last Name column. If your file only has a full name column, add the split columns before uploading and skip the combined one.
Custom fields cannot be mapped. The dropdown only offers the standard fields listed above, so custom fields your workspace has configured are not filled by an import. Set those on the records afterwards.
A row holds a single work experience and a single education entry. To import a full career history, use a CV upload or the Chrome extension instead, or enrich the candidates after the import.

​
Example file

A file with these headers imports cleanly, without any manual remapping:
candidates.csv
Spott maps Job Title to Work Experience Title, Company to Work Experience Company, and City to Location. The same file works for a contact import: the company column is what links each contact to their client company.

​
Complete the import

Confirm the mapping to start the import. Spott creates a record for every row. After the import completes, the records appear on the Candidates or Contacts page and can be searched, filtered, exported, and added to Lists.
An import creates records, it does not update them. When a row matches an existing person, that person is still added to the Job or List you selected, but their existing data is not changed by the import.
Company names need an exact match. When a row has no other unique identifier, companies are matched on name only. Matching is case-insensitive but otherwise exact: “Acme” and “acme” match, “Acme” and “Acme BV” do not. Spott does keep a manually curated list of aliases for well-known companies (so “Accenture GmbH” and “Accenture PLC” resolve to the same company), but for names not on that list, anything that does not match exactly creates a new company record.

​
Tips for successful imports

  • Include at least one unique identifier per person. Email or LinkedIn URL is recommended, so Spott can deduplicate against existing records.
  • Map first name and last name for clean records.
  • Remove empty rows before uploading.
  • Use UTF-8 encoding for CSV files for best compatibility.
  • Use a consistent date format across the file, ideally YYYY-MM-DD.
  • Double check email and phone mappings to avoid data landing in the wrong field.
  • Importing into a job adds the people as applications, but cannot set their application status or add comments. Set those in the pipeline after the import.
A LinkedIn URL column imports the link to the person’s profile, not the profile content itself. To pull in full LinkedIn profile data, use the Chrome extension or enrichment after the import.
Migrating a full database from another ATS or CRM is a different job, and our team runs it for you. See Data migration.