I have a couple of suggestions to get you started, but I want to say that the best way to start to learn segmentation is to export some data from your database — say, the results of your most recent initiative — open it in Excel, and just look at what you see. Sort the list by donation size. How many large gifts are there? How many small gifts? Do you notice clumping around certain numbers? Look at the addresses of the donors — are more from certain places than others? These are basic questions, but they are the first step towards viewing your donors as individuals rather than as one anonymous whole. I’ll write more on that in coming weeks, but the message is: Don’t be afraid to play with your data! You won’t break anything, I promise.
Now, as for the recommendations, I always start with two books. The first is the reassuringly titled Statistics Without Tears by Derek Rowntree. You’ll like this book immediately just by its size — unlike most statistics texts, you can carry it with one hand. It looks at you non-threateningly, as a small puppy might. It is a classic book, first published years ago, and there’s something comforting about the type and the graphs. It reminds me of cookies and tea at Grandma’s. More than the appearance, though, is the content. You may sweat a bit in places, but there will be no crying, and you’ll come out the other side knowing a bit more about the things you know you should know (what is a median, and why does it matter; what does the standard deviation measure, and why shouldn’t you be afraid of the word “deviation”) but don’t.
The second is the much more recent but excellent Fundraising Analytics: Using Data to Guide Strategy by Joshua Birkholz. Unlike Rowntree’s book, this book was written after the secret consortium of business publishers decreed that all business books much contain a colon in their title. (Have you noticed this? The same rule applies to movie sequels.) But more importantly, this is a very recent and much-needed addition to the vast number of fundraising books on the market, most of which lack any real specificity when it comes to collecting data and understanding it, and a few of which are patently banal. Birkholz walks through a number of basic and more advanced analytics issues, including a treatment of RFM analysis and an introduction to regression. It won’t make you a statistics hero, but it will go a long ways towards improving your knowledge, particularly if you read it with an eye not only towards specific techniques, but towards how he approaches data and analysis more generally. High recommended.
Neither book is a cheap ticket, but both are worth it, and should get you started. Happy reading!