Automatic structuring and retrieval of large text files
Communications of the ACM
A theory of term weighting based on exploratory data analysis
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Logistic Regression Using the SAS System: Theory and Application
Logistic Regression Using the SAS System: Theory and Application
Using e-CRM for a unified view of the customer
Communications of the ACM - Digital rights management
Individual and group behavior-based customer profile model for personalized product recommendation
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Developing a semantic-enable information retrieval mechanism
Expert Systems with Applications: An International Journal
Toward a successful CRM: variable selection, sampling, and ensemble
Decision Support Systems
Mining changes in customer behavior in retail marketing
Expert Systems with Applications: An International Journal
Extracting Consumers Needs for New Products - A Web Mining Approach
WKDD '10 Proceedings of the 2010 Third International Conference on Knowledge Discovery and Data Mining
Rubik's cube watermark technology for grayscale images
Expert Systems with Applications: An International Journal
Unified collaborative filtering model based on combination of latent features
Expert Systems with Applications: An International Journal
Mining ideas from textual information
Expert Systems with Applications: An International Journal
Data augmentation by predicting spending pleasure using commercially available external data
Journal of Intelligent Information Systems
Web usage mining to improve the design of an e-commerce website: OrOliveSur.com
Expert Systems with Applications: An International Journal
Including spatial interdependence in customer acquisition models: A cross-category comparison
Expert Systems with Applications: An International Journal
Predicting e-commerce company success by mining the text of its publicly-accessible website
Expert Systems with Applications: An International Journal
Improved multilevel security with latent semantic indexing
Expert Systems with Applications: An International Journal
Technology classification with latent semantic indexing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Protecting research and technology from espionage
Expert Systems with Applications: An International Journal
Web mining based extraction of problem solution ideas
Expert Systems with Applications: An International Journal
Weak signal identification with semantic web mining
Expert Systems with Applications: An International Journal
Quantitative cross impact analysis with latent semantic indexing
Expert Systems with Applications: An International Journal
Semantic compared cross impact analysis
Expert Systems with Applications: An International Journal
Hi-index | 12.07 |
We investigate the issue of predicting new customers as profitable based on information about existing customers in a business-to-business environment. In particular, we show how latent semantic concepts from textual information of existing customers' websites can be used to uncover characteristics of websites of companies that will turn into profitable customers. Hence, the use of predictive analytics will help to identify new potential acquisition targets. Additionally, we show that a regression model based on these concepts is successful in the profitability prediction of new customers. In a case study, the acquisition process of a mail-order company is supported by creating a prioritized list of new customers generated by this approach. It is shown that the density of profitable customers in this list outperforms the density of profitable customers in traditional generated address lists (e.g. from list brokers). From a managerial point of view, this approach supports the identification of new business customers and helps to estimate the future profitability of these customers in a company. Consequently, the customer acquisition process can be targeted more effectively and efficiently. This leads to a competitive advantage for B2B companies and improves the acquisition process that is time- and cost-consuming with traditionally low conversion rates.