The True Value of Predictive Analytics

Predictive analytics streamlines and complements prospect research. Yet it can also produce candid insights that extend far beyond the obvious applications.

Based on numerous conversations with clients and other fundraising professionals, it seems the term “predictive modeling” has become a catchall phrase for a solution that delivers not much more than ratings and scores. As a result, the true nature and benefits of predictive analytics have been devalued.

In some cases, the process itself, which should really be a statistical endeavor, has also devolved.

Ratings derived from quick, off the shelf applications that are “predictive” in name only are imprecise beyond a reasonable degree of statistical certainty, and are of limited value in forecasting the potential for future support.

True predictive analytics is based on custom-built statistical models that take into account an in-depth analysis of constituent behavior, including comprehensive past giving data and historical giving patterns as well as external demographic and socioeconomic data. A proper analysis like this takes time, and reliable results simply are not derived from any kind of push-button solution.

Check out Connor’s webinar, which covers the true value of predictive analytics as it was originally conceived: that is, as a genuine analytical process and a solution that delivers far more than just ratings and scores.

The webinar covers the distinction between true predictive analytics and “solutions” that pose as such but cut corners–to the detriment of the end user.

It’s well known that predictive analytics streamlines and complements prospect research. Yet it can also produce candid insights that extend far beyond the obvious applications. Less obvious yet actionable insights that can be gleaned from a true predictive analytics engagement include:

• diagnostics that provide a view of the overall health of your development program;
• benchmarks of your development program against institutional peers;
• identification of programmatic weaknesses and inefficiencies; and
• support for the case for creating, bolstering, or reinvigorating components of your development program.

We should view predictive analytics as a comprehensive solution and diagnostic tool set that enables you to assess campaign readiness; decide where to focus time, energy, staff, and other resources once a campaign is underway; inform portfolio, pipeline, and moves management; drive programmatic and management decisions; increase operational efficiencies; and enrich the data within your database.