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
3. 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 Webhook node.
4. Make sure the fields in your file have a corresponding Property in your Workspace.
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 |