Using the principles of RFM and lifetime value analysis, we examine behavioral patterns and make predictive models. Adding reliable demographic data reveals characteristics useful for more precise list selection and media planning. Donor performance is analyzed in terms of each factor that builds the historical giving behavior. Segmenting donors according to behavior helps pinpoint groups that need attention in order to increase overall revenue. Included with the RFM analysis is the predictive modeling tool which projects the effects on future revenue when certain variables change.
Data Mining of Purchase/Giving History
Identify trends within database segments to extend lifetime value and create precise marketing strategies.
Using historical data, we build interactive spreadsheets that predict customer behavior and revenue while maintaining complex interconnections