 We always want to create the best portfolios for our front-line fundraisers, to position them for success. In our quest to create high quality portfolios, we often encounter obstacles that make it challenging or even halt our progress entirely. Three of the most common obstacles can be overcome, with a bit of planning, strategy, and tenacity.
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 I have, in earlier years, shown my raw statistical results with my clients, hoping to share the joy of getting a beautiful statistics result. Their reaction was to look up from my PowerPoint and blink at me. My own cardiologist once showed me a series of dots in random spaces across the page, 2 inches deep, scattered all over. He told me that it was clear evidence of how my heart was doing. I looked up at him and blinked. Neither I nor he were getting our point across when we showed those untranslated results.
For example, I added below the output from a linear regression model. It should never be seen by a gift officer or an executive.  This blog post will get published after the end of the fiscal year for most nonprofits, but the ideas in here can still be used to help boost any campaign end (or start or middle, for that matter). Here we’ll review five ways you can push new prospects into your pipeline.
In our recent Water Cooler Chat, Greg Duke, Partner for Database Services, shared the Monte Carlo technique – a way of understanding what the likely range of results would be for a given scenario. In our blog post today, we expand on the concept of using this forecasting technique to take care of three different fundraising needs.
 In our recent Water Cooler Chat, we talked about using IRS data to understand charitable giving among US residents. Of course, that afforded me an opportunity to make lots of graphs and charts to study this data more deeply. Here is a look at some interesting statistics related to different US states.
First, notice in this graph that California, Texas, and New York all have the highest levels of median income, but are also the states where people claimed a negative adjusted gross income (see how the little red boxes drop below zero). |
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