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Overview: This paper presented in SUGI30 addresses developing predictive models using SAS/Enterprise Miner and SAS/STAT to give lists with a higher response rate. SAS software is sufficiently powerful to do both analysis of past campaigns and produce predictive models. The results of a campaign on both churn and contract renewal were analyzed using a life table approach. Models treating churn and contract renewal as competing events using both proc logistic and proc neural were developed and evaluated. This research is an intermediate level presentation and audience should have knowledge of base SAS and conceptual familiarity with regression.
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