TAILIEUCHUNG - Cookbook Modeling Data for Marketing_3

Tham khảo tài liệu 'cookbook modeling data for marketing_3', khoa học xã hội, kinh tế chính trị phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | The following code uses PROC TABULATE to create the decile analysis a table that calculates the number of observatic each decile the average predicted probability per decile the percent active per responders target of Method 2 model 2 rate target of Method 2 model 1 and the active rate target of Method 1 . titlel Decile Analysis - Activation Model - One Step title2 Model Data - Score Selection proc tabulate data weight smp_wgt class mod_dec var respond active pred records activ_r table mod_dec Decile all Total records Prospects sum f comma10. pred Predicted Probability mean f activ_r Percent Active of Responders mean f respond Percent Respond mean f active Percent Active mean f rts 9 row float run In Figure the decile analysis shows the model s ability to rank order the prospects by their active behavior. To clarify prospect s probability of becoming active is considered its rank. The goal of the model is to rank order the prospects so as true actives to the lowest decile. At first glance we can see that the best decile 0 has as many actives as the worst d Docile Analysis - Activation Model- One step This model is targeting adh Model Data - Score Selection Prospects Predicted Probability Percent Active of Respenders Percent Respond Percent Active Decile 36 483 0-00467 0 1 36 499 0-10010 2 36 483 3 36 486 4 36 436 5 36 484 6 36 498 7 36 485 0 00064 0-00069 8 36 496 0 00051 0-00044 9 36 494 Total 364 911 model data the best decile Figure Decile analysis using model data. Page 117 9 . And as we go from decile 0 to decile 9 the percent active value is monotonically decreasing with a strong decrease in the first three .

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