The client described the buying habits and buying trends desired in new subscribers. The optimal candidates were individuals likely to be repeated purchasers of ‘best of class' leisure time items, demonstrating not only available disposable income but also the likelihood of continuation of desirable purchasing trends. Given these metrics, Nautilus Systems identified and acquired commercially available demographic and financial data. Specific product and service categories were analyzed and assigned weights based upon their desirability. For example, certain types of titanium mountain bikes, or membership in certain types of golf club would be considered to have the appropriate status-conscious image, and would be assigned a greater weight.

Nautilus Systems used its proprietary data mining techniques to extract transaction data matching these product and service categories from commercial database sources, and by examining buying trends contained within mercantile databases of credit card purchases. The requested metrics were programmed into an on-line analytical processing (OLAP) program. A transaction database was built from the data sources, and its contents were run against the OLAP program.

Individuals fitting the desired profiles with regard to their buying habits and purchasing trends were extracted. The developed list was then run against the client's current database of cardholders to eliminate mailings to them, and the income and employment of the candidates were verified. The mined data were further analyzed using statistical methods, and the geographic distribution of the resulting information was plotted. Nautilus Systems delivered the final analysis as a geographic information system (GIS) presentation, mapping the distribution of the potential cardholders. Finally, the addresses of the remaining candidates were verified and rerun again the metrics before the final list was generated.