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The data was divided into two subsets as determined by the 'Approached for Upsell' variable. There were 270 customers who were approached for upsell during February 2018 – February 2019, while the remaining 2847 customers were not approached for upsell during this time period. We first split the data into two sets: one containing customers who have been approached for upsell in the past and one containing customers who have not yet been approached. Using the subset of customers who were already approached for upsell, the data was then split into a training and test set with a 70%/30% split, so the training set had 190 observations and the test set had 80 observations. The evaluation of performance metrics was done using repeated k-fold cross-validation with k = 10 using 3 repeats. The trained and tested model was then applied to customers who have not yet been
approached. This would result in the generation of new targets
which would then be ranked based on whether they have a high probability of choosing to upsell. There will of course still be a set of untargeted customers which the model will not recommend for approach. |
IEEE/ICACT20220017 Slide.08
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