Customer Lifetime Value (CLV) is considered one of the most useful measures for business to consumer (B2C) companies, often considered more valuable than other measures like conversion rate and average order value. An accurate CLV can be used to determine which customers to prioritize with marketing messages and discount offers. In this talk, Mr. Abbott will describe non-parametric machine learning approaches to calculating customer value (CV)—rather than CLV—that accommodate additional features not typically used in CLV models. Additionally, Mr. Abbott will also describe effective regression model accuracy metrics for customer value that extend beyond typical R^2 and RMSE.