A few years ago, I set out on an adventure: I wanted to learn R.
R is a statistical language and software package that is open source — this means the software and following updates are open to the public for free use. I was intrigued, so I signed up for a series of courses on a purveyor of massive open online courses and got started.
The introductory course was informative, and I was tracking with the content. But when I started the advanced courses that went through specific coding techniques and the context of all the statistical analysis was biomedical and healthcare data, I hit a wall. I could not code well. I did not understand any of the problems that the class was attempting to solve. Consequentially, I gave up on R.
Looking back, the series of courses presumed you knew how to code and use statistical software well, but did not know how to apply it to concrete business problems. I needed the opposite. This I found in Ashutosh Nandeshwar and Rodger Devine’s textbook on using R in advancement, "Data Science for Fundraising: Build Data-Driven Solutions Using R."
In "Data Science for Fundraising," the assumption is that the reader understands the basic concepts and needs for data analytics in advancement, but needs the tools, knowledge and support to do so. The book starts out with a review of how to build a case for analytics adoption in your advancement office and the beta tests you can design to show how analytics can solve specific advancement problems.
You do not need to come in knowing Python or having completed introductory courses on coding in R. What you do need to understand is your advancement office, the data you have and the problems you need to solve.
The application of R to advancement needs forms the second half of the book, and it is where the book excels. The book is immensely practical. The discussion of theory is kept to a minimum, and the explanations are focused on how to use R with your data. This is done through step-by-step how-to guides that give you the snippets of code you need to get going — this alone makes the book extraordinary. You do not need to come in knowing Python or having completed introductory courses on coding in R. What you do need to understand is your advancement office, the data you have and the problems you need to solve. You can then use the provided code and illustrations to analyze your own data.
Take the “Predicting Gift Size” chapter as an example. The chapter starts out with a simple forecasting model that can be built, and by the end of the chapter, you have walked through building multiple models for comparison using techniques like Neural Networks or Gradient Tree. Most R resources go in-depth on the theory behind Gradient Tree and Neural Networks, but in "Data Science for Fundraising," the how and why is kept to a minimum so that the what — the product you can use to make data-driven decisions — can take the lead. Basically, the key tenet of this book is that a prospect development professional does not need to understand the proofs or statistical theory that go into supervised machine learning techniques or Random Forest. They just need to understand how to create a product that answers business questions using data analytics.
Whether you are hoping to have data analytics as part of your prospect development repertoire in the future or already have several seasoned analysts on your staff, I recommend "Data Science for Fundraising" as a training and professional development tool to add to your prospect development library.
Thomas Turner is the director of research and prospect management at International Justice Mission where he manages a team that provides research, relationship management and reporting to all global advancement teams. He was co-lead on the organization's Salesforce implementation.
Currently, Thomas is the mentorship chair on the Apra DC Metro board, and serves on the Apra International Editorial Advisory Committee and Advocacy Committee. He is also on the advisory board for the Center for Christian Civics in Washington, D.C.
Rodger Devine, one of the authors of "Data Science for Fundraising," will be presenting a session at the Data Analytics Symposium next month. Check it out!
And if you're looking for a deep dive into science science from your computer, download the Apra University Data Analytics Bundle 1. You will get five data analytics-focused sessions for a discounted price, including "Prospect Analytics: Separating Fact from Fiction" and "Leveraging Geographic Data for Prospecting."