document: Customer targeting models using actively-selected web content 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 incorporating 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 .
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