Importing Customers From CSV

If you have a list of customers you wish to import into your account, navigate to “Settings -> Imports” and then select “Import from CSV file”.

Click “Import customers” and then click this link to download a sample file.

I use Microsoft Excel for editing the csv files but if you don’t have Excel on your computer, you can use the free online version of Excel or “Google sheets” to edit your csv file. Please find a link to the online versions of Microsoft Excel and Google sheets in the description below the video .

When I open the file, some of the contents are not fitting in their columns. The trick is to click on the triangle at the top left corner and then double click the line between the headers, to auto resize all the columns. Note that all the columns are adjusted now.

If your phone numbers start with zero, like mobile numbers in Australia or UK, save your file as Excel before any edits. Microsoft Excel removes the leading zero before the numbers when saving csv files. Once you finished your edits, you can save the file back into csv to import.

The sample import file is designed for basic import including email, 3 phone numbers for customers, address and some notes.

In addition to the basic fields, you can add:

  • The date and time customer has been added
  • Additional custom data about the customer like Age, Gender, Measurements or Preferences.

To enter the date and time customer created, you can simply add a new column called: InsertDateTime and then enter your date and time as:

Year, dash Month, dash Day, then T, hour, colon minute, colon second.


For example this is how to enter: 2018 October 26 at 17:42:27:


Your custom data can be added by creating columns starting with Ext and then a number, like Ext1, Ext2 and so on.

Geelus will ask you to map these columns to your “Extra fields” when importing your file.

To demonstrate the import, I’m going to add InsertDateTime column and enter the dates following the above format. If you already have a date column, you can select the entire column and then use “Format Cells” in Excel to format the column. The date format in excel must be YYYY-MM-DDTHH:mm:ss

I’m going to add a new column called “Ext1” which will map to customer’s age. And Ext2 to map to Gender.

I will enter the age under Ext1 and customer’s gender under “Ext2”.

Now I go back to Geelus to create the extra fields to map my extra columns to.

Extra fields can be created under “Settings -> Extra fields”.  Click plus and then enter the name. Please choose the name of your extra data column carefully as you should not change it later.  I enter “Age” here.

The target for the extra data is “Contact”. Note that you can also add extra data to your transactions using the same method.

Under the Type, I click “Text” and leave the default value empty. I click check to create the new extra field. Then I choose “Yes, add now” to add it to my register.

I  do the same for Gender but this time I choose “Select/Combo” for the type. I click plus to add 2 options: Male and Female.

My extra columns are created and my file is ready, so I go back to imports and select the file. Now I can map my Ext1 and Ext2 columns to my extra data columns I’ve created in the last step. Click Upload to upload the contacts list.

I have only imported 2 customers so it was fairly fast but if you have thousands of customers in your list, it might take a few minutes. My contacts are now imported into my account, so I should be able to search them under “Transaction history” or “New transaction” page. You can see that the insert date time as well as age and gender has been imported successfully. I can get a report of all my customers under “Reports-> customers-> customers list”. Clicking on any customer will show the customer details, including the extra data we added.


CSV (Comma Separated Format) files can be edited using a simple notepad app (not recommended), Microsoft Excel or Google sheets. If you don’t have Excel or Google Sheets, please find the links to use the online versions (free) below:

  1. Microsoft Excel:
  2. Google Sheets: