Method and apparatus for advertising bidding
First Claim
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1. A method for determining a bidding strategy for placing a plurality of bids for a plurality of marketing options, the method comprising:
- performing, by one or more computing devices;
determining empirical data associated with marketing options based on performance metrics of the marketing options and based on observation of web site traffic from user devices to computing resources that expose the user devices to the marketing options;
generating a predictive model that comprises one or more statistical models, wherein the predictive model is generated based on the empirical data;
determining at least one modeling parameter for the predictive model, wherein the at least one modeling parameter is variable and is associated with at least one of a user characteristic or a marketing option characteristic;
determining at least one objective for the predictive model to optimize;
receiving a trigger event to optimize the predictive model, the trigger event associated with web site traffic to a set of web sites;
optimizing the predictive model by solving an objective function based in part on the at least one modeling parameter, the at least one objective, and at least one constraint; and
determining, in real time relative to the trigger event, the bidding strategy based on the optimization of the predictive model, wherein the bidding strategy comprises a set of the marketing options that results in the optimization in accordance with the at least one modeling parameter, the at least one objective, and the at least one constraint, the set of the marketing options used in connection with subsequent web site traffic to the set of web sites.
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Abstract
Methods, articles, and systems for determining a bidding strategy for on-line query answer set or contextual advertisement positions for marketing options is described herein.
39 Citations
20 Claims
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1. A method for determining a bidding strategy for placing a plurality of bids for a plurality of marketing options, the method comprising:
performing, by one or more computing devices; determining empirical data associated with marketing options based on performance metrics of the marketing options and based on observation of web site traffic from user devices to computing resources that expose the user devices to the marketing options; generating a predictive model that comprises one or more statistical models, wherein the predictive model is generated based on the empirical data; determining at least one modeling parameter for the predictive model, wherein the at least one modeling parameter is variable and is associated with at least one of a user characteristic or a marketing option characteristic; determining at least one objective for the predictive model to optimize; receiving a trigger event to optimize the predictive model, the trigger event associated with web site traffic to a set of web sites; optimizing the predictive model by solving an objective function based in part on the at least one modeling parameter, the at least one objective, and at least one constraint; and determining, in real time relative to the trigger event, the bidding strategy based on the optimization of the predictive model, wherein the bidding strategy comprises a set of the marketing options that results in the optimization in accordance with the at least one modeling parameter, the at least one objective, and the at least one constraint, the set of the marketing options used in connection with subsequent web site traffic to the set of web sites. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 20)
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10. A non-transitory computer-readable storage medium storing program instructions executable on a computer to implement a bidding strategy system configured for:
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determining empirical data associated with marketing options based on performance metrics of the marketing options and based on observation of web site traffic from user devices to computing resources that expose the user devices to the marketing options; generating a predictive model that comprises one or more statistical models, wherein the predictive model is generated based on the empirical data; determining at least one modeling parameter for the predictive model, wherein the at least one modeling parameter is variable and is associated with at least one of a user characteristic or a marketing option characteristic; determining at least one objective for the predictive model to optimize; receiving a trigger event to optimize the predictive model, the trigger event associated with web site traffic to a set of web sites; optimizing the predictive model by solving an objective function based in part on the at least one modeling parameter, the at least one objective, and at least one constraint; and determining, in real time relative to the trigger event, a bidding strategy based on the optimization of the predictive model, wherein the bidding strategy comprises a set of the marketing options that results in the optimization in accordance with the at least one modeling parameter, the at least one objective, and the at least one constraint, the set of the marketing options used in connection with subsequent web site traffic to the set of web sites. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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17. A system, comprising:
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a non-transitory computer-readable storage medium; and one or more processors coupled to the non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores program instructions executable by the one or more processors to implement a bidding strategy system comprising; a modeling component for; determining empirical data associated with marketing options based on performance metrics of the marketing options and based on observation of web site traffic from user devices to computing resources that expose the user devices to the marketing options; generating a predictive model that comprises one or more statistical models, wherein the predictive model is generated based on the empirical data; determining at least one modeling parameter for the predictive model, wherein the at least one modeling parameter is variable and is associated with at least one of a user characteristic or a marketing option characteristic; and an optimizer component for; determining at least one objective for the predictive model to optimize; receiving a trigger event to optimize the predictive model, the trigger event associated with web site traffic to a set of web sites; optimizing the predictive model by solving an objective function based in part on the at least one modeling parameter, the at least one objective, and at least one constraint; and determining, in real time relative to the trigger event, a bidding strategy based on the optimization of the predictive model, wherein the bidding strategy comprises a set of the marketing options that results in the optimization in accordance with the at least one modeling parameter, the at least one objective, and the at least one constraint, the set of the marketing options used in connection with subsequent web site traffic to the set of web sites. - View Dependent Claims (18, 19)
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Specification