When choosing whether and how much to donate, potential donors often observe a set of default donation amounts known as an “ask string.” In an experiment with more than 400,000 PayPal users, we replace a relatively unused donation amount ($75) on PayPal’s Giving Fund Website ask string with either a lower ($10) or a higher ($200) reference point to evaluate the impact on charitable giving. Relative to the status quo, we find that a higher reference point increases the total amount of money raised, while the lower reference point increases the number of donors, two objectives important to non-profits. Both interventions drive more people to choose a default amount compared to the status quo, where the alternatives are not donating or writing in an amount. Examining treatment effect heterogeneity and changes in the distribution of donations, we provide suggestive evidence about the mechanisms. We use data-driven machine learning methods to learn personalized policies that identify who should be shown the lower versus higher reference point. Personalization can increase the probability of choosing a default amount, and it can also alleviate the trade-off to non-profits between the total amount of money raised and the number of donors.
