Donor Retention in Online Crowdfunding Communities: A Case Study of DonorsChoose.org

Abstract

Online crowdfunding platforms like DonorsChoose.org and Kick-starter allow specific projects to get funded by targeted contributions from a large number of people. Critical for the success of crowdfunding communities is recruitment and continued engagement of donors. With donor attrition rates above 70%, a significant challenge for online crowdfunding platforms as well as traditional offline non-profit organizations is the problem of donor retention. We present a large-scale study of millions of donors and donations on DonorsChoose.org, a crowdfunding platform for education projects. Studying an online crowdfunding platform allows for an unprecedented detailed view of how people direct their donations. We explore various factors impacting donor retention which allows us to identify different groups of donors and quantify their propensity to return for subsequent donations. We find that donors are more likely to return if they had a positive interaction with the receiver of the donation. We also show that this includes appropriate and timely recognition of their support as well as detailed communication of their impact. Finally, we discuss how our findings could inform steps to improve donor retention in crowdfunding communities and non-profit organizations.

Keywords: Crowdfunding; Donor Retention; User Retention.

Figure 1

Example project request from DonorsChoose.org. Every project page contains the project title (a); the teacher and school (b); an essay by the teacher about their students, their project, and their specific need (c); the remaining amount to fund the project and the number of donors who have given already (d); needed materials in itemized form (e); and more information about the school and its students (f). This project asks for art supplies for a primary school in New York City.

Figure 2

Fraction of donors by number of total donations by the donor. Note the log scale of the Y axis. 74% of donors donate exactly once and do not return. 26% return for a second donation and 14% do not return afterwards. Only 1% of donors make five donations. Online crowdfunding is facing the same attrition problem as offline NPOs.

Figure 3

Whether or not the first project is successful is strongly correlated with retention for both teacher-referred and site donors. Donors whose first project succeeded are 5% more likely to return and donate again. Note: The error bars in all plots represent 95% confidence intervals on the corresponding mean estimate.

Figure 4

First-time donors to small projects are much more likely to return than donors to large projects. This effect could be explained through having a greater sense of personal impact when fewer people make the project succeed.

Figure 5

The propensity to return as a function of the number of projects by the same teacher in the future. Teacher-referred donors (blue) are less likely to return than site donors (red). Both types of donors are much more likely to return if they donate to (future) “high-profile” teachers.

Figure 6

Retention rate across donors located at varying distances from the projects they funded with their first donation. Local donors are generally more likely to return and distant site donors are particularly loyal to DC.org as well.

Figure 7

Top: Donors that donate last to projects are much more likely to return than other donors (for successful projects). Early donors are more likely to return than middle ones. Across all project sizes we observe a consistent “U-shape”. Bottom: Early donors tend to be local and late donors tend to be distant.

Figure 8

Donors expressing commitment to DC.org through generous donation amounts are more likely to return. Donors opting out of supporting DC.org and making small donations are surprisingly loyal to the site (see the text for details).

Figure 9

(Top) Teacher-referred donors are less likely to return to the site as the teacher posts new projects over time. For site donors, the effect levels off after an initial decrease in retention rate. (Bottom) Both teacher-referred and site donors are less and less likely to return to the same teacher over the “teacher lifetime”.

Figure 10

Effect of giving thanks through a confirmation note right after project becomes fully funded. Top: Donor return to site. Bottom: Donor return to same teacher. The dashed lines represent the respective average return rates.

Figure 11

Effect of communicating impact through an impact letter. Top: Donor return to site. Bottom: Donor return to same teacher. In all cases, timely communication is very strongly correlated with donor return. The dashed lines represent the respective average return rates.

Figure 12

Donors that donate to teachers who allow DC.org to publish posts on their behalf are significantly more likely to return. However, the effect persists for both local and distant as well as teacher-referred and site donors suggesting that this is not a causal effect (see text for details).

Figure 13

Model calibration plot of predicted probabilities of donor return against empirical probabilities showing that the Logistic Regression model using all features predicts well-calibrated probabilities.