Lapsed or Dormant? Leveraging Statistical Analysis in Fundraising

Rather than trying to flag lapsed and dormant donors using casual heuristics, formal statistical analysis can be brought to bear on this question. A recently published paper by Peter S. Fader, Bruce G.S. Hardie and Jen Shang, “Customer-Base Analysis in a Discrete-Time Noncontractual Setting,” examined exactly these kinds of trade-offs using annual donation data from a major public radio station. It showed remarkable accuracy in predicting donation patterns over a five-year forecasting horizon. While the model has some complex math within it, the ultimate implementation is a relatively simple Excel spreadsheet, requiring nothing more than recency and frequency as inputs. Many of the results and implications within the paper run quite contrary to the usual intuition that many nonprofit organizations have about the behavioral propensities (and thus future contributions) of their past donors. For instance, the paper found that recency is far more important than frequency in determining estimates of future donation patterns.