Is Predictive Analytics at the Tipping Point?
It has been my mantra that predictive analytics is within your reach. Although the science comes out of the academic community, the products are designed by the experts, and the development was ushered by math geeks, it is time for the user to step up. The tools are increasingly user-friendly and you know your data better than anyone.
It seems we are at the point where the leading fundraising organizations are building data mining programs rapidly. By the increasing size of the campaign totals, I can understand why. The tools are there. The necessity is clear.
The organizations that have built predictive analytics programs are likely more efficiently identifying prospects, applying effective segmentation strategies, understanding their constituents, making smart data enhancement decisions, and raising more money.
The business world agrees:
Business intelligence and decision support have been utilized by organizations for several decades. Their deployment continues to spread in both breadth and depth within many of these organizations while gaining new converts in others. However, data mining, and its application as predictive analytics, has often been characterized as a technology that could only be utilized by highly skilled technical practitioners with strong statistical backgrounds...This may have been true in the past, but is arguably no longer the situation today.
Read More
It seems we are at the point where the leading fundraising organizations are building data mining programs rapidly. By the increasing size of the campaign totals, I can understand why. The tools are there. The necessity is clear.
The organizations that have built predictive analytics programs are likely more efficiently identifying prospects, applying effective segmentation strategies, understanding their constituents, making smart data enhancement decisions, and raising more money.
The business world agrees:
Business intelligence and decision support have been utilized by organizations for several decades. Their deployment continues to spread in both breadth and depth within many of these organizations while gaining new converts in others. However, data mining, and its application as predictive analytics, has often been characterized as a technology that could only be utilized by highly skilled technical practitioners with strong statistical backgrounds...This may have been true in the past, but is arguably no longer the situation today.
Read More
Labels: Analytics Implementation
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