Big Data, Crowdfunding and the Fundraising Technology Craze
“All in all, we walked away from this campaign very excited and energized,” McCarthy says. “It created an experience for people that really felt interactive and creative, and reminded people about community and what mattered to them. That’s what really drove this.
“It’s very different than just sending somebody a wallet envelope or giving them a link to your online giving form. This was almost like an event, a virtual giving event,” she adds. “From that perspective, we felt like this was very much a good thing to do. It created a lot of good will, and it was really fun for everyone.”
McCarthy says that while Vassar probably won’t embark on crowdfunding campaigns that often, it will most likely continue to do one annually. And she feels crowdfunding campaigns are best for short campaigns with specific deadlines and goals, which is why the Vassar500 became the Vassar1000 and succeeded and vastly surpassed its goal.
JDRF’s Big Data Management
Managing a donor database is difficult no matter the size of an organization or its donor base. However, when you are a large, international nonprofit organization, particularly one with chapters across the U.S. in addition to six international affiliates, managing data in a uniform, centralized fashion is even more complex.
JDRF, the leading global organization funding type 1 diabetes research, is one of those large, international nonprofits handling data across different chapters spanning the globe.
“We realized we had a ton of software systems,” says Megan Martin, former director of data analysis at JDRF. “We had lots of places to collect and manage data, but it was disjointed. It wasn’t efficient to use the data to answer the strategic questions we wanted to answer.”
Having so many systems in so many different places made it difficult to pull everything together. JDRF had reports everywhere, Martin says. Every system had its own report, staffers kept their own Excel files and some people were looking at different reports, leading to confusion. For instance, one person may have been looking at an older report that was filtered to show just U.S. donors, while her colleague was looking at an updated report that included international support.