The administrator of an NFP organization manages their donor database in Raiser’s Edge, a popular data management software application for fundraisers. They also use another software package, Constant Contact, to capture information about people participating in various events and marketing campaigns. A third set of data comes from online donor activity by credit card. The problem is how to manage and integrate the different data sets that contain some overlapping and some inconsistent data.
As one would expect when integrating different datasets, there are numerous format or spelling inconsistencies within the names and addresses, multiple phone numbers, emails, and so on. Additionally, there can be multiple people in the same location. Are these the same person? Partners or spouses? Have people moved? What is the correct information?
A FreeSight solution (model) was created that automatically imports the three sets of data, cleans and formats all names and addresses into a consistent field structure for analysis. It then segments all of the data into two groups – those that are clearly unique individuals and addresses, and those that have duplications in some way, whereupon rules are applied to determine the priority order of data selection. Obvious duplicates are removed, and those that are not obvious are identified for personal attention.
Out of 10’s of thousands of records, the manual database clean-up chore is reduced to only a few hundred records. The database clean-up task that would have taken weeks to complete manually was reduced to three hours. And now, because this FreeSight model exists, the next clean-up chore will only take minutes. Importantly, because the mailing database is now clear of duplicates, the organization’s direct mailing costs have been reduced considerably as well.