Making Offers to Customers (Self-Learning)
The Self-Learning Response Model (SLRM) node generates and enables the updating of a model that allows you to predict which offers are most appropriate for customers and the probability of the offers being accepted. These sorts of models are most beneficial in customer relationship management, such as marketing applications or call centers.
This example is based on a fictional banking company. The marketing department wants to achieve more profitable results in future campaigns by matching the right offer of financial services to each customer. Specifically, the example uses a Self-Learning Response Model to identify the characteristics of customers who are most likely to respond favorably based on previous offers and responses and to promote the best current offer based on the results.
This example uses the stream pm_selflearn.str, which references the data files pm_customer_train1.sav, pm_customer_train2.sav, and pm_customer_train3.sav. These files are available from the Demos folder of any IBM® SPSS® Modeler installation. This can be accessed from the IBM SPSS Modeler program group on the Windows Start menu. The pm_selflearn.str file is in the streams folder.
Existing Data
The company has historical data tracking the offers made to customers in past campaigns, along with the responses to those offers. These data also include demographic and financial information that can be used to predict response rates for different customers.
