I want your thoughts of using Survival Analysis and Survival Regression model for the following use-case (in travel industry) :
- How long before departure date (and after booked date) is ideal to promoting certain types of extras?
Here the "duration" is fixed ie Gap between Booking and Departure Date and the "birth" can be considered the booking of main product and "death" can be considered booking the "extra" (Correct me if I am wrong)
"Censorship" (and observed=0) happens:
(A) when no "extra" is booked and the customer travels without it (B) when customer cancels the entire booking before departure date
I want your thoughts on the following:
- Does it make sense to see how the survival function pans out for the population? You think i could use the median survival time to get a ideal time for promoting extras? How else could I use the survival analysis function?
- Can I use a survival regression model to predict at a customer level what would be their median survival time and then use it for customized promotions?
One thing to note that the dataset is biased towards Observed=0 (% of customers booking extras is quite less than who book extras).. Will it break any assumptions?
Should I balance the dataset by selecting dataset with extras and without extras?