Scary Data Frankensteins

When you are reviewing fundraising data, beware any time the data contains information from two different media channels or two different audiences. 

Here’s a simple example…

Say we recently completed a campaign that included one appeal letter to current donors and two e-appeals.  Here are the results:

• 11,000 sent
• 124 gifts
• 1.4% response rate.

With those numbers, we can get a vague sense of whether the campaign was successful.  But I would say that the data above hides more than it illuminates because when we go to run the campaign next year we don’t know how to improve the campaign because we don’t know which parts of the campaign worked, and which parts didn’t.

But look at what happens when we can see the results for each piece of the campaign…

Direct mail appeal letter to current donors

• 1,000 sent
• 83 gifts
• 8.3% response

E-appeal #1

• 5,000 sent
• 31 gifts
• .62% response

E-Appeal #2

• 5,000 sent
• 10 gifts
• .20% response

OK, now we’re talking.  Look at what we know now:

• The appeal letter is a tremendous success.  An 8.3% response in direct mail is fantastic.
• E-appeal #1 is also a success – a .62% response in email is also a success.
• E-appeal #2 is not a success – a .2% response is too low.

Compare that to the combined data, which gave us an average response rate of 1.4%.  That number didn’t tell us anything.

But looking at the performance data for each piece enables us to do something powerful: learn that the messaging used in the appeal letter and e-appeal #1 worked great, and then apply those the next time we do this campaign and to all our future fundraising.

Additionally, by breaking out the results for each piece, over time you’ll learn your benchmarks for each audience and each channel.  This is very powerful because it helps you identify the pieces of fundraising that are effective, and those that aren’t.

But if you keep everything together, you just get a Frankenstein.