Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign
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Updated
Dec 30, 2022 - R
Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign
A data-driven tool to identify the best candidates for a marketing campaign and optimize it.
Predictive State Propensity Subclassification (PSPS): A causal deep learning algoritm in TensorFlow keras
Propensity model to predict a customer's likelihood of purchasing a product from an online store based on past behaviour
A repo with functions for building various COMs and GCOMs quickly.
The feature of interest is whether or not a customer buys a caravan insurance, based on socio-demographic factors and ownership of other insurance policies; and to build profile of a typical customer.
Propensity Modelling and RFM Analysis to predict users' likelihood of making a purchase.
Sales prediction for a segment of product.
Explores the relationship between population demographics, various crime rates, and shall carry gun laws across different regions of the United States between 1977-1999 using a propensity weighted mixed linear effects model.
An insurance company has a historical data set (train.csv). The company has also provided a list of potential customers to whom to market (test.csv). From this list of potential customers, the model determines whom to market and whom not to.
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