Customer targeting models using actively-selected web content

Prem Melville, Saharon Rosset, Richard D. Lawrence
2008 Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08  
We consider the problem of predicting the likelihood that a company will purchase a new product from a seller. The statistical models we have developed at IBM for this purpose rely on historical transaction data coupled with structured firmographic information like the company revenue, number of employees and so on. In this paper, we extend this methodology to include additional text-based features based on analysis of the content on each company's website. Empirical results demonstrate that
more » ... orporating such web content can significantly improve customer targeting. Furthermore, we present methods to actively select only the web content that is likely to improve our models, while reducing the costs of acquisition and processing.
doi:10.1145/1401890.1402003 dblp:conf/kdd/MelvilleRL08 fatcat:fbsdkwqwunhjhpoovaw4nydiim