Mortgage Loan Debt Consolidation
Back in November I mentioned the importance of cleaning up your existing prospect pool. So, now that you have deactivated those who are not really prospects and have identified those with true affinity, what is next? Now may be the time to take on a database screening. Screening can mean different things to different people. For some it means finding wealth, for others it means determining who is likely to give and at what level.
Wealth screening is also known as “list matching.” Names from your database are “screened” against names in external databases to find matches. The matches then return financial, biographical and philanthropic giving information. A score, indicating the reliability of the match, is also returned so that you can be sure that your John Brown is the same John Brown with the 10,000 shares of stock in XYZ company. If the screening company also provides information on constituents’ gifts to other organizations, you may get some indication of philanthropic intent.
Data modeling also uses lists but not for one-on-one matching for wealth. At a very basic level, it applies mathematical formulas to existing statistical information such as the U.S. Census, credit reports, and IRS giving data to predict giving among groups of people. A group might just be a zipcode or a city or state. Data modeling can also incorporate information about your constituents to make it more meaningful. Sometimes a wealth screening is performed as part of this more tailored approach. A score, indicating whether the prospect is a major gift or an annual fund prospect, is returned for each of the names screened. Finally, there is a third level of data modeling that involves a customized model based on the characteristics of your database and donor pool. This model is considered by many to be the most accurate but it is also the most expensive.
Which of the screening/modeling methods is best for your organization? We’ll try to provide some tools to help you reach that decision in an upcoming blog.
We are all have debt, its true.
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