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4.30. What are the import fields in NewPanda?

Updated 01.08.18

Use the DOWNLOADS link on this page to download a sample Excel spreadsheet with column headers for the importable fields in NewPanda.  You may need to format or "clean up" data from other sources to get it into compatible import fields for NewPanda.

NOTE: DATE fields (Birthdate, Home Anniversary Date, Wedding Anniversary date) MUST be in the following format:  mm/dd/yy OR mm/dd/yyyy

We've had lots of requests over the years to make our fields "match" the fields of other CRM programs and apps.  We've designed the fields in the NewPanda app to help you create beautiful eMarketing messages and social updates with our own product features and capabilities.  I'm sure you have noticed that NewPanda isn't like ACT!, Goldmine, Outlook, Palm, Access, SalesForce.com (shall we continue?).  That's probably part of what attracted you to NewPanda.  Remember that as with any other app or program, a certain amount of "setup" is always required (we like to refer to this as "data TLC").

Unfortunately we can't manipulate your data for you to get it into importable shape.  It's not that we don't love you.  But for liability purposes, we just can't be responsible for making sure your data is the way you want it.  Your data is the most important aspect of your eMarketing efforts, even more important than the tools you use to deliver your messages. 

That said, it naturally follows that making sure your data is clean, up-to-date and accurate is the most important step in setting up your NewPanda tools.  We can't tell by looking at your data whether it's right, wrong, old or new.  We don't know if what you've got for Mary's mobile number is really her mobile number or her home number.  Our Text Messaging feature obviously requires the right type of data to be in the Mobile Number field.  So you see, it's just best that your data is managed by the person that knows the most about your data, whether that's you or one of your associates.  Remember, good eMarketing cannot happen without good data. 

We hope you'll take some time at the very outset to give your data the love it needs.  Why? 

The benefits will be well worth the initial effort!


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