1. A computer-implemented method comprising: receiving a list of keywords via a data network interface for processing by a processor of a computer system; ordering the list of keywords from high activity to low activity, the high activity corresponding to keywords with a statistically significant number of return on investment (ROI) events, the ROI events corresponding to revenue-generating events; modeling the keywords based on a set of variables, the modeling including generating a revenue per click (RPC) value prediction for each of the keywords, the RPC value prediction being based on the set of variables, past keyword revenue performance data, and historical bid density by category for each keyword, the modeling including region specific modeling to improve the regional accuracy of the RPC modeling; scoring the keywords based on the modeling; and clustering the keywords based on the scoring, wherein the RPC value prediction being further based on a category of first activity for users who have converted on a given keyword.