This is a very relevant post as it applies directly to my job. As I respond to this post, I am about to complete my fifth models all developed in JMP Pro 12 using variety of data types. Once the model has been developed in JMP, I used the model to score customers who have similar historical context as those customers whose data that were used to develop the model. Once I the scoring process is done to those customers and I than retrieved their responses from whatever products/services they were promoted with in the past and using the predicted scores from the scored data table plus their actual responses, I sort the predicted scores from largest to smallest and rank the customers into decile of 10.
For example, the most targeted customers would be those in the decile 1, follow by decile 2, 3, 4, etc computing other stats in JMP such as their # of Customers, Response Rate (RR%), Actual # Enrollments, Gains %, Surplus ($), $/Piece, Average $ Amount, etc. Using these stats, we make business decisions which customers to target and who we shouldn't.
We use this process to also assess how well the model is performing in predicting reality by including the actual responses and using the curvature of the decile, which monetarily should decile from 1-10. This extract assessment process is purely exclusive of the internal JMP model validation process. Once we are all good with the model performance and the curvature of the curve of the decile depth chart.
The next step in the process is to deploy the model. Right now,I just download the Customer IDs along with other essential data fields such as the Model Score, Model Decile, Model Name into a text file, we than gets loaded into the data warehouse, which then becomes available to the marketing department for campaign segmentation, campaign analysis, targeted marketing formulation. In the near future, plan is to work internally to use JMP open database connectivity platform to load model tables directly to the marketing data warehouse.@Jeff Perkinson
Jenkins Macedo