When importing data to Silverbucket it is vital to keep the structure identical to the example datasheet to ensure a flawless import:

- First row contains the names of the headers - it is not necessary to edit the first row.
- Second row in your file is where your data starts to get imported
- Columns need to be in the same exact order as in the examples
- Rows after the default structure's last column are never read / handled when importing
- Never have hidden columns in your data sheets

- Customers with extended data: name, street address, postal code, city, country, businesscode, website

List of customers can be found in Customers > Listing.
The extended data can be found in the Customer's Dashboard:

col. A	B	C	D	E	F	G	H
Name of the customer (mandatory)	Street address for the customer	Postal code for the customer	City for the customer	Country of the customer	Customer's business code	Customer's Website	Customer's Code

1) A new customer called 'City of Helsinki'. Columns B, C, D, E, F, G are added to the Customer's Information fields in its dashboard.
2) A new customer called 'City of Vaasa'. Columns D, E are added to the Customer's Information fields in its dashboard. Columns B, C, F, G are skipped and left empty.

Silverbucket matches rows to Silverbucket's data case-sensitively ("SilverBucket_Support" is not considered the same as "silverbucket_support").
However, matching email fields is done case-insensitively ("Support@Silverbucket.Com" is considered the same as "support@silverbucket.com" when creating a user, for example)

If the data structure was correct, you can see the outcome in Silverbucket right after the upload. To make sure all went fluently, you can search for the desired customer in Silverbucket; in this example we searched for the City of Helsinki: