You Should Run More Experiments
Testing assumptions in the field can avoid costly errors in decision-making.
You Should Run More ExperimentsWe present a complete empirical case study of fundraising campaign decisions that demonstrates the unique importance of in-context field experiments. We first design novel matching-based fundraising appeals. We then discuss the assumptions needed to derive theory-based predictions from the standard impure altruism model and solicit expert opinion about the potential performance of our interventions. Both theory-based and experts’ predictions suggested improved fundraising performance from framing a matching intervention as crediting donors for the matched funds, whereas predictions for the other appeals were more ambiguous. However, the results of a natural field experiment with prior donors of a nonprofit instead showed a significantly poorer performance from employing the giving-credit framing. This surprising finding was replicated in a second natural field experiment to confirm the ground truth, at least within a specific context. Experts also lacked consensus about a conditional matching scheme, which, in fact, did not improve fundraising. Theoretically, our results highlight the limitations of both impure altruism models and expert opinion in predicting complex warm-glow motivation. More practically, our results question the availability of useful guidance and suggest the indispensability of field testing for behavioral interventions in fundraising.
Published in: Marketing Science
Testing assumptions in the field can avoid costly errors in decision-making.
You Should Run More Experiments