“Work smarter, not harder.”  Yeah, easy for you to say!  Those of us who work with nonprofit organizations on a daily basis have seen that hint of an eye roll when we even come close to suggesting such a thing. Why?  Simply put, it often seems to be much easier said than done.

Prospect screening poses an interesting conundrum in this endeavor:  Organizations seek our assistance in an effort to do just that—pursuing, in essence, their low hanging prospect fruit. But, unfortunately, upon receiving the screening results, the message they hear is “There is no magic bullet.”  In other words, you can’t just take a simple score or rating, drop it into an appeal and “Voile!”, expect magical results.  The disappointment is unmistakable.  “What?? I thought that’s why I hired you guys!”

Alas, don’t despair!  You didn’t make a mistake in undertaking a screening project.  You can, indeed, work smarter and find that low hanging fruit through prospect screening.  You just have to have a clear picture of how the results fit into an overall prospect identification plan.  What is often missing from the disappointed response is an understanding that, in development, working smarter means having a multi-faceted approach to prospect identification.

Historically, prospect identification was typically reactive, primarily based on giving.   Since this capitalizes on a donor’s propensity to give, it certainly isn’t a bad first step.  Then, prospect research, and specifically, the use of wealth information, tipped the scales a bit to the capacity side of things.  With prospect screening touting the integration of propensity and capacity, the obvious expectation was that the results would, indeed, be that magic bullet.  But a good prospect identification system avoids using scores and ratings in a vacuum.

So, what do I suggest?   I like to illustrate an A + B + C + D + E approach.  How does this work?  Consider the legend below:
A = Likelihood results based on predictive modeling
B = Ask range based on predictive modeling
C = Wealth/asset results
D = Past Giving
E =Anecdotal information, such as Peer Screening information

Ideally, screening results and summary wealth information has been added to your CRM.  Once there, querying for this information should be a straightforward process.  The results will, indeed, become a bit of a magic bullet, using your screening results in tandem with other known information. You have now balanced accuracy with efficiency.   The prospects identified will help you achieve that goal of working smarter, not harder.

So what is your methodology for finding that low-hanging fruit?  I would love to hear it.  Share your thoughts in the “Comments” section of this blog or email me at laura.worcester@blackbaud.com.

ABOUT THE AUTHOR

Laura Worcester, senior consultant at Target Analytics, joined Blackbaud in 2001.In her current role she advises nonprofits on utilizing screening results in identifying and evaluating best donor prospects. In 25+ years of fundraising experience, Laura has served as the chief advancement officer for numerous organizations and managed her own consulting business, providing grant writing services to arts, educational and health care organizations. She’s presented at development conferences and has been a regular contributor to Blackbaud’s blogs with selected posts being reprinted in journals such the NonProfit Times. A traveler since her study abroad days in Denmark, Laura’s committed to passing this enthusiasm on to her teenage daughters. Her family’s travel adventures were just featured in a neighborhood magazine in her suburban Milwaukee community. Contact Laura by email.

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