Customer Life Time Value (CLTV) is one of the most critical themes in the Customer Analytics domain. This talk covers various approaches to building CLTV models and how the insights from these models can be leveraged to run targeted campaigns.

There will be discussions around datasets required to perform analysis and the modeling framework(s). The talk will also cover RFM analysis, common features relevant to build models and various modeling techniques including classical statistical distributions that model survival and counts processes.

A few case studies where these models have been implemented will be reviewed and challenges associated with applying the models will be discussed as well.