2017-07-31

Data Mining for Fund Raisers

This is a repost of a Goodreads' review I did a little over 4.5 years ago, for a book I read twelve (12) years ago, which seemed relevant, as the industry seems to be picking up a data-driven focus. Plus, the world is now being transformed by advances in machine learning, particulary deep learning, and the large data sets and complexity of donor actions should greatly benefit from analysis.

Data Mining for Fund Raisers: How to Use Simple Statistics to Find the Gold in Your Donor Database Even If You Hate Statistics: A Starter GuideData Mining for Fund Raisers: How to Use Simple Statistics to Find the Gold in Your Donor Database Even If You Hate Statistics: A Starter Guide by Peter B. Wylie

My rating: 4 of 5 stars

My spouse, at times a development researcher of high-net worth individuals, was given this book because she was the 'numbers' person in the office. Since my undergraduate was focused on lab-design, including analysis of results using statistics, I was intrigued and decided to read it. Considering my background, I found some of the material obvious, while other aspects were good refreshers on thinking in terms of statistics.

Below is the synopsis I wrote at the time:

Purpose of Book
How the Process Can Improve Endowment Activities
Outline of Method (Non-Technical)
  1. Export sample of donor database
  2. Split sample into smaller components
  3. Find relationships between donor features and giving
  4. Select the significant variables
  5. Develop scoring system
  6. Validate findings
  7. Test finding on limited appeals and compare results
Assumptions
Limitations
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