What data-driven tactics are OK? A quick note.

An uproar about data modeling was in full swing the last few days. The NYT reported that Target uses data to, well, target customers. It got one wrong (spilling the beans about a daughter’s pregnancy to her father!) by getting it right (quickly gathering, analyzing and distributing marketing based on data points that knew more about the daughter than the dad). The data screening and data modeling trends have long taken hold in our industry. Now we are starting to see even more potentially questionable applications of data taken from the corporate world, raising some base questions: What about privacy? What about effectiveness? What about competitive advantage? What about creeping people out?

This raises the question: how far can and should data analysis go in fundraising? As a card-carrying member of APRA, I value research, analytics and prospect management. Data are the fuel for fundraising. As a father, or as a recipient of seemingly countless fundraising calls from poorly trained solicitors via robo-dialing, or as a donor, I wonder everyday where fundraisers should draw the line.

This topic–what data is “available” and how can/should we use it to raise money–is increasingly salient because data points are increasingly available. How should you sort through the details? Here is my three-point quick assessment approach:

  1. My starting point is typically not just can you raise money with a data-driven tactic but will the tactic build relationships?
  2. In the long run, gimmicks and disingenuous strategies deliver fewer results than donor-centric and mission-critical approaches. Which is it?
  3. But, it may not be long before unheard of tactics become commonplace approaches. Do benefits outweigh risks?

So, the short answer to this profound question is that focusing on relationships first should provide the answer for your organization’s approach to what data and when. I’m planning a more thorough look at the topic later this year (HIPAA, FERPA, national do not call lists, consumer data applications, and more). In the meantime, I welcome your cases, conundrums, and ideas.

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