AAA Auto Club South’s Ernesto Diaz and Kristin Rahn on Efficiently Building Predictive Models
TM: Where is AAA Auto Club South gaining efficiency in building predictive models?
KR: Because the user interface tool is so easy, that's where we save time in building the models. But once we have the model, it lets us export code to score everything in batch. So all the scoring can be done in jobs overnight. ...
ED: Right now ... our focus is on increasing productivity of building the models. And, like Kristin said, having the tool is very user-friendly and efficient in doing that so that we can batch-feed this information at night and still get a significant improvement. Whether it's at call centers or whether it's just getting in front of who the customer is at the call center or the branch or doing direct mail and, ultimately, when we're working online.
TM: What advice can AAA Auto Club South provide to marketers who would like to build similar predictive models?
ED: One of the things that we focused on on the membership attrition side was ... the relationships that we had with the members at the time that the model was run. ... What we try to understand is at the time that we are making the decision to send direct mail, that's the time where we go back. And one of the things that we go back to understand is, first of all, the demographics. So to what extent the demographics play a role in a customer's propensity to renew or not renew. The other thing is to what extent does the relationship play a role to renew or not renew. And what I mean by the relationship is: the types of products that they have used, the number of times they have used the product and so on. So … that kind of data was the data we generated to provide to the modeling engine to then determine what are the variables that are most likely to help us understand whether a person will renew or not.