Data Import Best Practices

Practical guidance for preparing and cleaning CSV data before importing it into Seen Platform.

1. Make sure the data is clean

Cleaning your data before importing significantly reduces unwanted videos generated in the platform.

• Remove leading and trailing spaces in all cells
• Remove unwanted spaces inside cells: Ole-Christian and not Ole- Christian
• Remove unwanted characters: e.g. !@#$%^&*(),.?":{}|<>[ ]\;'~_1234567890`
• Consistent casing: Daniel and not DaNIeL
• Unified formatting for numbers: e.g. all values 100 000 or 100000 or 100,000
• Remove all rows with missing data (e.g. missing first name)
  • You can also replace bad or missing data with a generic option, if the script allows this.

2. Remove unused data

Remove any columns or fields you don't actually use for personalisation. Leftover data increases the chance of mapping errors and makes the file harder to review later.

3. Include an internal ID

Include an internal ID (e.g. ID-number or email address) for you to be able to match rows from the exported file from the Platform in your system for distribution, or to use in the Project Webhook.

4. Make sure the fields in your file have a corresponding Property

Fields in your file need a corresponding Property in your Project.

5. Make sure to use the following filetype

• CSV
• UTF-8 with comma Delimited
• One header row

6. Example file structure

crm_id	first_name	last_name	interest
123	John	Doe	Football
234	Jane	Smith	Tennis
345	Michael	Johnson	Basketball
456	Emily	Davis	Swimming
567	William	Martinez	Volleyball
678	Elizabeth	Taylor	Skiing
890	James	Anderson	Golf
020	Jennifer	Thomas	Badminton
046	Robert	Jackson	Football
352	Linda	Harris	Rugby
782	David	Martin	Cricket
365	Barbara	Thompson	Ice Hockey
289	Richard	Garcia	Baseball
033	Susan	Martinez	Table Tennis
078	Joseph	Robinson	Cycling