The Planned Giving Blogger

The art and science of planned giving.

Audience selection redux: Part I

with 3 comments

There is probably no more perplexing question in planned giving marketing than ‘who should I be mailing to’?  I’ve previously blogged on this topic but since it is such an important question and since the answer is so complex and nuanced, I think it’s worth more ink.

I’m prompted to write on this topic now because I ran into Chuck Longfield at the recent DMA Nonprofit Federation conference.  Chuck was the brains behind the Passion Index created years ago by Target Analytics.  Although now spending much of his time with his kids and on his philanthropic work, Chuck is still serving as Chief Scientist for Blackbaud, which acquired his companies. Then, right after I saw Chuck, I read an interview with Peter Wylie entitled “Adjusting Your Gaze” on the CASE website.  In it, Wylie, the author of books and reports on data mining for fundraising, also tackles this subject.

I asked Chuck about his latest thinking on planned giving audience identification and he confirmed his earlier research showing that transactional information on donors, what he refers to as passion indicators, are still the most powerful data available.  When coupled with external, appended data, segmentation models become especially powerful, providing guidance on both propensity and capacity.  External data alone typically address the capacity question.  And, as we all know, just because a donor has capacity doesn’t mean he or she will make large gifts to our organization.  It’s the passion indicators that help identify donors who might.

Wylie shares this view.  In response to a question about wealth screening, he notes, “Those services are aggregating public information. It will tell you who is rich, what are their stock sales, what are their real estate holdings. But just because your alumni have money doesn’t mean they’re going to give it to you.

Why aren’t you looking at what you already know about these prospects? Your proprietary data is so much richer than anything you are going to find out from a public-records search. Wealth screening is one tool, but to my mind it is a supplement to data mining, not a replacement for it.”

Tomorrow I’ll address the next logical question:  “What data elements are important?”


P.S.  To read earlier posts on the subject click on the Categories drop down on the right side of this page and select Audience Segmentation.


Written by Phyllis Freedman

February 8, 2010 at 11:27 pm

3 Responses

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  1. Hopefully, the next logical question should be this: how often do you visit your donors? Planned giving officers (or any other development pro) who don’t ever leave the office cannot possibly cultivate a relationship with donors. It can be high-maintenance and time-and-labor intensive, but it’s worth it. And your donors, especially those who will be giving so much, are deserving of the extra time and effort.

    steffan cress

    February 9, 2010 at 6:07 am

  2. […] a comment » Yesterday’s post revisited the question of transactional data (propensity) vs appended data (capacity) for […]

  3. Phyllis: I’d like to address your future question, ‘what data elements are important’. You quoted Chuck Longfield as saying that ‘transactional information on donors’ is key. I’d agree, but when I read ‘transactional’ I assume he means giving history. I may be misinterpreting, but in any case my point is that patterns of past giving are only part of the picture when it comes to indicators of ‘passion’. Event attendance, number of times the alum has updated their contact info, the amount and types of info an alum has shared (such as email and business phone) – these and many other data points are likely to be correlated with planned giving potential. Putting them together can be powerfully predictive. As well, the degree of correlation will differ from institution to institution, so there’s no one list of sure-fire predictors for everyone. I’ve written a bit on the subject here:


    February 10, 2010 at 12:48 pm

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