In Chapter Nine of the The Why Axis, Uri Gneezy and John List examined some of the conventional wisdoms about the techniques used in charity fund raising to try to determine if they really work at all, as well as which work better than others. What are the motivations for people to give to charity? How might these motivations be exploited to get people to donate more?
The authors noted that in their travels, that most charities rely on the assumptions and conventional wisdoms of the previous decision makers, “rather than verifiable data.” One of the conventional wisdoms John came across was idea of “seed money.” The idea is that you communicate to donors how large or small “seed” is compared to the goal to get donors to donate more. The question is how large or small of a seed to gets people to donate more. For instance, if you communicate that you have already reached 10% of your goal, will people donate more or less than if you said that you had already reached 33% of your goal or 50% or 67%. One of the conventional wisdoms was that 33% was the magic number. They found that while having a seed did increase the donations, this 33% wasn’t the magic number. When they said their seed was 67% of what they needed, the contributions increased compared to the lower seed values. The thinking is that people give more because they think that if the charity has already raised more money from other people, the charity is good. They call this the “follow-the-leader effect,” which seems to overwhelm the “free-rider effect,” the idea that the more other people have given to a charity, the less you would have to for them to reach their goal.
Another strategy charities use is the matching grant; for every dollar you donate, an anonymous benefactor will match your donation. Gneezy and List tested whether different matching ratios would work better 1:1, 2:1 (for every dollar you donate, the benefactor will donate 2) 3:1, 4:1 and a control (no matching donation). What they found was that between the control group and the matching groups, matching groups made 20% more in donations. However, against the conventional wisdom, the ratio of the matching donation didn’t matter; the 1:1, 2:1, and 3:1 were all roughly the same.
Among some of their other findings were that tontines could raise more money than a conventional lottery, especially for people with different tastes in potential prizes (tontines could give different prizes) and for more risk adverse people (tontines provided a higher opportunity for payouts, even if they were smaller than the lottery). They also found different methods companies could use to get their employees to save more for retirement without actually increasing the amount the company matches for the 401k.