Tuesday, August 16, 2011

BIG’s Blog: Predictive Analytics – Part 1

Today’s blog is for my subscribers that have large direct mail fund raising programs. This is my promised follow-up to my Monday blog about the reality of the failing Postal Service and the very real chance that the USPS will begin to raise the postage rate that nonprofits pay. Before this happens, it is my fervent hope and strong suggestion that your organization gets serious about adopting predictive analytics.

IBM is a long-established technology company when compared to other technology giants like Oracle, Microsoft and Google. A lot of people don’t know that IBM is now betting the company on Information Technology and Analytics. And the big push is analytics. IBM targets the largest corporations in the world and frankly is not interested in selling to the nonprofit industry; however, there is much nonprofits can learn from what IBM is doing with the Fortune 500 when it comes to predictive analytics.

So, what is predictive analytics? A recent IBM paper by Eric Siegel, PhD. gives an excellent definition: Predictive analytics is business intelligence technology that produces a predictive score for each customer (read donor) or other organization element. Assigning these predictive scores is the job of a predictive model which has, in turn, been trained over your data.

For years, nonprofit direct mail fund raisers have used RFM (Recency, Frequency and Monetary) as the three key elements for segmenting and targeting. But, with the ability to capture donor behavior information in donor management systems, and the availability of demographics information that can be appended to donor records, not to mention the proliferating amount of online data, there was suddenly a need to have more data points considered for targeting purposes.

Analytic tools and methodologies make sense of the data. With predictive analytics, direct mail fund raisers can learn from its cumulative experience (data) with donor interactions and take the actions to apply what’s been learned.

For nonprofit direct mail fund raisers, this means that as mail becomes more expensive, you must develop predictive models that only target those donors with the highest propensity (predictive scores) to give.

Nonprofit direct mail fund raisers need to start thinking more like insurance companies when it comes to managing risk. Like insurance, nonprofit direct mail fund raising is an exercise in risk management. The decisions of who to mail and who not to mail impacts the risk the direct mail fund raising organization must withstand, such as the risk of a donor defecting, or not responding to an expensive mailing, or of not being selected to be targeted for telephone or email follow-up.

Just like insurance companies, nonprofit direct mail fund raisers would benefit from measuring, tracking and computing core risk as a key part of their direct mail programs.

Friday we will review how long predictive analytics has been around.


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