Mapping tells EasyDigz which of your columns holds which piece of information. It guesses first, and you confirm.
Bulk Upload Contacts
Import contacts from a CSV or Excel file.
| EasyDigz Field | Your File Column |
|---|---|
| First_Name * | first_name |
| Last_Name * | last_name |
| Email * | |
| Phone | mobile |
| Billing_City | city |
| Birthdate | Skip |
5 of 6 columns matched automatically. Nothing imports until you confirm.
The table lists the EasyDigz field on the left and asks which of your columns feeds it, not the other way round. Once you see it that way the screen makes sense immediately.
#What it detects on its own
Names, whether one column or separate first and last, email addresses, phone numbers, birthdates, countries as names or codes, ZIP codes and billing addresses. It copes with different date formats and address conventions, and works even when your file has no header row.
#Fixing a wrong guess
- 1
Find the EasyDigz field in the list.
- 2
Change the dropdown to the correct column from your file.
- 3
Set anything you do not want to Skip.
An unmapped field is not an error, plenty of imports have no birthdate.
- 4
Continue when the table reads correctly.
#Separate first and last name columns
If your file splits them, they can be combined into a single full name during mapping, you do not need to merge the columns in your spreadsheet first.
#Which fields matter
| Field | Importance |
|---|---|
| The most important. It is how you email them and how duplicates are detected | |
| Name | Needed for anything personalised |
| Phone | Useful, optional |
| Birthdate | Only needed if you plan to use the birthday trigger |
| Address fields | Useful for geographic segmenting |
Mapping is a preview. You can go back, change it, and see the effect before a single record is created.