Text Mining to Identify Customers Likely to Respond to Cross-Selling Campaigns
Gregory W. Ramsey, Sanjay Bapna · International Journal of Business Analytics · 2016
This paper reports on the results of extracting useful information from text notes captured within a Customer Relationship Management (CRM) system to segment and thus target groups of customers likely to respond to cross-selling campaigns. These notes often contain text that is indicative of customer intentions. The results indicate that the notes are meaningful in classifying customers who are likely to respond to purchase multiple communication devices. A Naïve Bayes classifier outperformed a Support Vector Machine classifier for this task. When combined with structured information, the classifier performed only marginally better. Thus, customer service notes can be an important source of predictive data in CRM systems.