| 摘要 |
The present invention provides a "Keyword Automated Bidding System" which, among other things, provides an intelligent system for bidders for a ranking in web search results list to determine bids and bidding strategies that maximize return on bid investments and help direct allocation of available funds for bids to keywords that lead to more optimal returns. In one possible embodiment, the present invention is designed to generate a scalable solution to the problem of selecting the proper set of keywords to bid and the proper values of such bids for thousands of keywords on third party sites such as Overture and Google.com. The satisficed solution is generated according to operator-defined model constraints and utility functions. In one embodiment, KABS maximizes profit by maximizing the Margin Rate to a bidder which is the difference in the aggregate Revenue per Redirect (RPR) from the merchants and the Cost per Click (CPC) we must pay the traffic source. The prime constraint on this solution is the total CPC dollar amount that is budgeted over a fixed interval of time (day, week, etc.). A major computational subsystem of KABS performs the estimation of arrival or click-thru rates for each keyword or category of keywords as a function of their display ranks on the source site. It is the form and level of this estimated function that is critical in the selection of the proper display rank from an active bid table our spider retrieves for each keyword. The KABS operator will be required to provide the inputs that direct and constrain the system's operation. Among these is the comprehensive set of keywords of interest from which the proper subset will be computed. Other key inputs include the frequencies of executing the various KABS from recomputing the arrival functions to regeneration of the bidset of keywords along with their corresponding bids and display ranks.
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