KALMAN FILTER MODELING IN ONLINE ADVERTISING BID OPTIMIZATION
First Claim
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1. A method for use in association with an auction-based online advertising exchange, the method comprising:
- using one or more computers, obtaining a set of historical advertisement impression information associated with a set of previously served advertisement impressions, comprising profile information and revenue-related performance information;
using one or more computers, using a Kalman filter-based model to forecast revenue-related performance of each of a set of possible advertisement impressions over a future period of time, comprising using, as input to the model, at least a portion of the historical advertisement impression information, including at least a portion of the profile information and at least a portion of the revenue-related performance information;
using one or more computers, obtaining as output from the model, and storing, forecasted revenue-related performance information relating to each of the set of possible advertisement impressions over the future period of time;
using one or more computers, using the forecasted revenue-related performance information in facilitating determining an optimized bid in connection with a first advertisement impression opportunity to be served during the future period of time; and
storing optimized hid information relating to the optimized bid.
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Abstract
The present invention provides methods and systems for use in bid optimization in connection with advertisement serving impression opportunities available in an auction-based online advertising exchange. Methods are presented in which, based in part on historical advertisement performance information, a Kalman filter-based model is used in forecasting performance of a set of possible advertisement impressions served over a future period of time. Forecasted performance information is used in determining an optimized bid in connection with an available opportunity.
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Citations
20 Claims
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1. A method for use in association with an auction-based online advertising exchange, the method comprising:
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using one or more computers, obtaining a set of historical advertisement impression information associated with a set of previously served advertisement impressions, comprising profile information and revenue-related performance information; using one or more computers, using a Kalman filter-based model to forecast revenue-related performance of each of a set of possible advertisement impressions over a future period of time, comprising using, as input to the model, at least a portion of the historical advertisement impression information, including at least a portion of the profile information and at least a portion of the revenue-related performance information; using one or more computers, obtaining as output from the model, and storing, forecasted revenue-related performance information relating to each of the set of possible advertisement impressions over the future period of time; using one or more computers, using the forecasted revenue-related performance information in facilitating determining an optimized bid in connection with a first advertisement impression opportunity to be served during the future period of time; and storing optimized hid information relating to the optimized bid. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A system for use in an online advertising exchange, comprising
one or more server computers coupled to a network; - and
one or more databases coupled to the one or more server computers; wherein the one or more server computers are for; obtaining a set of historical advertisement impression information associated with a set of previously served advertisement impressions, comprising profile information and revenue-related performance information; using a Kalman filter-based model to forecast revenue-related performance of each of a set of possible advertisement impressions over a future period of time, comprising using, as input to the model, at least a portion of the historical advertisement impression information, including at least a portion of the profile information and at least a portion of the revenue-related performance information; obtaining as output from the model, and storing, forecasted revenue-related performance information relating to each of the set of possible advertisement impressions over the future period of time; using the forecasted revenue-related performance information in facilitating determining an optimized bid in connection with a first advertisement impression opportunity to be served during the future period of time; and storing optimized bid information relating to the optimized bid in at least one of the one or more databases. - View Dependent Claims (14, 15, 16, 17, 18, 19)
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20. A computer readable medium or media containing instructions for executing a method comprising:
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using one or more computers, obtaining a set of historical advertisement impression information associated with a set of previously served advertisement impressions, comprising profile information and revenue-related performance information; using one or more computers, using a Kalman filter-based model to forecast revenue-related performance of each of a set of possible advertisement impressions over a future period of time, comprising using, as input to the model, at least a portion of the historical advertisement impression information, including at least a portion of the profile information and at least a portion of the revenue-related performance information; using one or more computers, obtaining as output from the model, and storing, forecasted revenue-related performance information relating to each of the set of possible advertisement impressions over the future period of time; using one or more computers, using the forecasted revenue-related performance information in facilitating determining an optimized bid in connection with a first advertisement impression opportunity to be served during the future period of time, comprising; determining at least one of the set of possible advertisement impressions that is most similar to the first advertisement impression opportunity for the purpose of determining an optimized bid in connection with the first advertisement impression opportunity; and determining an optimized bid in connection with the first advertisement impression opportunity based at least in part on the at least one of the set of possible advertisement impressions; storing optimized bid information relating to the optimized bid; and implementing bidding in accordance with the optimized bid on an online advertising exchange.
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Specification