Relationship mapping analytics for fundraising and sales prospect research

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Third Sector Publishing (TSP) has been successful selling CharityCAN subscriptions to fundraising organizations across Canada. This has been the result of incorporating a large volume of data from different sources that prospect researchers find useful as they attempt to identify potential donors for their organizations. For example, the Canadian data that TSP licenses from Blackbaud, Inc. includes over 7.3 million donation records - records of donations that individuals, foundations, and companies made to which organizations. As well as licensed data, there is an abundance of publicly available data that will be useful to CharityCAN subscribers. TSP will be able to extract this data from websites through automated extraction processes. For example, most law firms in Canada create and post for free biographies of their lawyers. TSP will be able to add these biographies to the growing volume of useful data that already can be found on the CharityCAN platform. The challenge for CharityCAN is connecting this growing number of data points. Relationship mapping refers to the identification of relationships among individuals. Relationship mapping becomes particularly useful when it can predict the strength or weakness of any relationship. CharityCAN requires sophisticated machine learning algorithms and data mining tools that will identify relationships among individuals, private-sector companies, and non-profit institutions, and then these algorithms should be able to predict the strength (or lack thereof) of these relationships. As a result, various (complex) networks could be formed and, with this in hand, some hybrid clustering methods could be used to extract groups of users that are potentially of interest to the subscribing institution or company (for example, for personalized and targeted solicitation).