As a manager in Spark, you can create many user accounts at once using bulk import. This guide walks you through preparing your file, uploading it, and checking results.

Note: If you only need to create a single user account, see Create an Individual User

Before you start

• Prepare your user data in a single spreadsheet file (.CSV, .XLS or .XLSX). We recommend .CSV or.XLSX for the smoothest import.
• Ensure your organisational units are set up in Spark (you'll map users into these during import).
• Required columns (minimum): First Name, Last Name, Email address, or Mobile Number, and Organisation Unit. 

• Avoid blank rows, filters, colour formatting, or other workbook features that can break import.

  

  Click here for example file

Additional extra columns

• Tags (you can add tags per row - an import tag is automatically applied to every upload)
• Time Zone (if you need non-default time zones)
• Language (You can set the trainee language preferences on import)
• Any custom fields your LMS requires (custom fields must match platform settings)

Steps

1. Open the Users tab from the dashboard.

   

2. Click on the drop down icon next to Create new user and choose import users. 

   

3. Click Choose file select your spreadsheet, then click Continue. 

   

4. Spark will detect the file type and sample the columns and number of users. If the detection looks correct, click Continue.

   

5. Field mapping: Check that each field is matched to the correct column in your spreadsheet. Use the source field dropdowns to make adjustments. Leave non-required fields blank if they aren't included in your file )e.g. Mobile number).

   

6. Review value conversion: check any fields that need mapping. For example, match the organisation unit names in your file to the existing structure in Spark. You can also: add tags, and update user time zones

   Note: Spark automatically adds an import tag with the date. Keep track of this tag if you plan to assign training right after import.

   

7. Click Continue to move to the Review page. This page shows a summary of valid and rejected records. 

   

8. If there are rejected records, click View full details to see the validation error for each rejected row. 

   

   You cannot edit rows here. To resolve the errors, make adjustments to your source file and re-upload those records, or upload the rejected rows as a new import.

   

   Additionally, you'll see a downloadable report option. The report distinguishes between existing users (already in Spark) and new import errors. You can use this file to confirm which records were successful and which need fixing.

9. When the valid records are ready, click Import X valid users. This will create the user accounts in Spark. 

   

   Once the import completes, you'll get a confirmation message and an option to distribute training to the newly imported users. If you don't assign training now, you can use the auto-generated import tag or organisational units later.