Data Import Tips

Here are some tips and tricks for making sure your import is successful:

Numeric columns

Our Excel reader interprets all numeric columns as floating point numbers. This is good for currency amounts ($12.34), but not always what you want (postal codes, id numbers, etc.). To get around this, transform these columns to “text” columns in Excel before you save your file from Excel.

One other common numeric culprit is US zipcodes, especially those with leading zeros (e.g. “01234”). You should convert these columns to text before saving your Excel file.

Blank rows

Beware of blank rows in your uploaded file. We try to remove blank rows automatically, but the best practice is to remove all blank rows before uploading your file.

Make sure columns match up

Be careful that data is in the correct column. For example, if you have someone’s name in the “zipcode” column, you’ll have a hard time sorting this out later.

Whole Name vs. Name Parts

If you import a “whole name” field (e.g. “Joe Donor”), you probably don’t also want to import the name parts (e.g. first name: “Joe”, last name “Donor”). This is because Donor Tools treats the whole name field as a separate name, and will think you’re trying to import two names for each donor. You’ll end up with two names in each record. Instead, import either the Whole Name field or the parts of the name, but not both.

Dates

Our import tool does its best to guess the right date format from dates that you provide. However, because there are so many different formats that a date might be in, we occasionally get it wrong. For example, 01/02/2012, 02/01/2012, 01/02/12 are all common date formats, but they might each represent a different actual date.

To minimize the possibility of error, for date columns in your spreadsheet you should use a date format that explicitly spells out the month, day, and year of the date, such as February 1, 2012 or 1 Feb 2012. You can also use machine format, which lists the date in the order of year, month, day, like this: 2012-02-01.

Address and Name Labels

You can provide labels for names and addresses that you import. For example, you can import one email address with the label “Home”, and another with the label “Work”.

To do this, name the column in your spreadsheet with the label as you want it to appear in your database. For example “Work”, “Home”, etc. The label must match a built-in type or existing custom type as defined under Settings/Custom Data Types. This works for:

• Names
• Addresses
• Telephone Numbers
• Email Addresses