Think about the following scenario:
You log into your yahoo news page and click on a story about someone who has just lost their home. The story is a vivid, personal account of a hardworking woman who lost her good-paying job in the economic downturn and, after 9 months of no job, ended up taking a position making 1/2 of what she did before. The story goes on to tell of the impact her situation has had on her family, especially her children who are 4 and 2. She’s not quite sure where she will turn because she has no living family.
How would this story impact you?
Now, think about this scenario:
You log into your yahoo news page and click on a story about the rising number of homeless due to the economic downturn. The story is data-heavy, well-researched and makes the case quantitatively that homelessness is on the rise.
How would this story impact you?
Over the last few years, development folk have been convinced that we need compelling “outcome measures” in order to inspire donors to make significant gifts. For instance, we need to talk about how many students from our university go on to graduate school. The phrase “outcome measures” almost always has meant “quantitative data.” The argument is that this kind of quantitative proof is what moves donors to action. Quantitative data is “real” or “hard” data. Everything else is soft and not nearly as powerful to make a case for support.
But think about the two stories above. Which of the two encouraged you to be more sympathetic? Which of the two might be more apt to encourage you to give in response?
The stories of human drama, of success, of opportunity, and of growth and development are, ultimately, the outcome stories that move donors. Yes, we should be quick to highlight quantitative outcomes data too. But, never forgot that someone losing their home is far more compelling and sympathetic than the problem of homelessness.