Development of Predictive and Prescriptive Analytical Models Using Customer, Revenue, and Usage Data

Wu, Shiyu; Bazakas-Chamberlain, William; O'Connor, Michael; Kihu, Abigael

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Development of Predictive and Prescriptive Analytical Models Using Customer, Revenue, and Usage Data

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In collaboration with the WPI MQP team, SaaSWorks is pursuing the development of a predictive model that integrates client data into classifications that enable the identification of key performance indicators correlated with a customer's lifetime value. The model pinpoints which customers display patterns indicative of a high churn risk cancellation and distinguishes them from those periodically churning and reactivating, re-purchasing or re-subscribing. These analytics will be productized into a configurable product feature set that drives strategic decisions within SaaSWorks clients’ companies and assists in the automatic discovery of previously unknown key performance indicators.

This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

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