Cool, Simple Tests to Improve Fundraising

What do you do when you have limited resources and need to raise money? Test! Test to find out what works best, and then use those results to refine your strategy.

Far too often non-profits send letters, run events, and follow routines without ever knowing what works and what doesn’t. Here’s just one example from an interview with John A. List, professor of economics at the University of Chicago. List, who is a huge proponent of field experiments, says: “When you go and ask those charities if matching gifts works they say, “Of course it does, and a 2-to-1 match is much better than a 1-to-1 match, and a 3-to-1 match is better than either of them.” But, when he asked them “What is your empirical evidence for that?” They had none. Turns out that it was a gut feeling they had.”

This article is intended to get you to stop running on your gut feeling, and instead to do a little analysis to find out what actually works and refine your strategy accordingly. It’s not hard, we’ll tell you how.

Start with a good hypothesis

Before you jump into any testing, start out with a good hypothesis; a reasonable idea of what will work based on previous knowledge that can be tested. Over the years, we have given you a lot of valuable advice on how to write the perfect fundraising and thank you letter, how to create the perfect donor experience, how to design a donor-friendly website, how to improve marketing, and how to fundraise: strategy and dos and don’ts. This knowledge, combined with other facts and insights you have gained through the years about what might work, is a good place to start in building your hypotheses.

Example: “I think calling donors to give them an update on how their donations were used will result in higher subsequent donations.” This is a reasonable hypothesis that is backed up by data and can be tested.

Test, Test, Test

Once you have a reasonable hypothesis, the next step is to test. In the end, not all “truth” will be true for you.

In the case of matching gifts, once an experiment was performed, List found that “the match in and of itself works really well. We raise about 20 percent more money when there is a match available. But, the 3-to-1, 2-to-1, and 1-to-1 matches work about the same.”

This test involved 50,000 letters and a carefully planned out experiment. Likely your tests won’t be as sophisticated as this, but that’s ok. What’s important is that you are thinking strategically: constantly analyzing, finding out what works, and adjusting your strategy accordingly. Here are just a few examples:

  • If there is a low completion rate for the donation form on your website, and you’re wondering what’s going on, you can use A/B testing to find out if slight changes in the appearance, the text, or the layout have a positive impact on this rate. Google Analytics will help you track the success rate of each variation to determine which one works best.
  • Maybe you’re wondering why the open rates for your emails are so low. In this case, you can use A/B testing again to test different subject lines to see which ones result in better open rates.
  • You may also want to test solicitation letters this way. Test different appeals, ones using quotes from clients and ones using quotes from staff, ones asking for gifts starting at $10 and ones asking for gifts starting at $50.
  • Finally, if you’re having trouble inspiring donors to give again and give more, you may want to test different engagement strategies. Just last month, we gave you a few tests that showed how powerful the phone can be in inspiring subsequent donations. Maybe this will work for you too!

If you are committed to testing, you have put yourself on a path that is guaranteed to lead to success. This data will inform future decisions and help you become progressively smarter in the decisions you make for your website, email marketing, fundraising, events, and so on. Of course, performing these tests is not going to pay off unless you are tracking the results somewhere. Sumac will help with this.


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