Wallet Estimation Models

The wallet of a customer is defined as the total amount this customer can spend in a specific product category. This is a vital piece of information for planning marketing and sales efforts. We discuss the important problem of customer wallet estimation, while emphasizing the use of predictive modeling technologies to generate useful estimates, and minimizing reliance on primary research. We suggest several customer wallet definitions and corresponding evaluation approaches. Our main contribution is in presenting several new predictive modeling approaches which allow us to estimate customer wallets, despite the fact that these are typically unobserved. We present empirical results on the success of these modeling approaches, using a dataset of IBM customers.

By: Saharon Rosset; Claudia Perlich; Bianca Zadrozny; Srujana Merugu; Sholom Weiss; Rick Lawrence

Published in: RC23860 in 2006


This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.


Questions about this service can be mailed to reports@us.ibm.com .