Enhanced online advertising system
First Claim
1. A system implemented across a network having one or more publishing sites correspondingly associated with at least one publishing entity, each of the publishing sites comprising at least one publisher page having publishing content that is displayable to any user of the publishing site, and at least one available ad space, the system comprising:
- at least one processor programmed for;
storing a plurality of anonymous profiles that are associated with a plurality of users;
analyzing the displayable publishing content accessed from the publishing sites;
storing the results of the analysis of the accessed publishing content;
receiving from one or more advertising entities across the network and storing;
one or more selectable action objectives associated with one or more advertising sites correspondingly associated with the advertising entities, andone or more ads having selectable links from which each of the respective advertising sites can be accessed;
analyzing advertising content accessed from one or more of the advertising sites, wherein the advertising content comprises at least the ads received from the advertising entities;
receiving from a user terminal across the network an automated request for one or more ads associated with a display to a user associated with the user terminal of one of the publisher pages at the user terminal, the publisher page to be displayed comprising the displayable publishing content and one or more of the available ad spaces; and
determining if the analyzed publishing content is ready for matching to the stored ads;
wherein if the processor determines that the analyzed publishing content is ready for matching to the stored ads, the processor is programmed tomatch the automated ad request to at least a portion of the analyzed publishing content for the publisher page to be displayed;
statistically match the user to one of the stored plurality of anonymous profiles, using known information associated with the user, wherein the known information comprises any of location, gender, age, interests, purchases, usage patterns, or other prior actions by the user;
predict a response to the ads by the user, wherein the prediction is at least partially based on the matched stored profile and any of the analyzed publishing content and the analyzed ads received from the advertising entities, and wherein said prediction comprises a predicted impression revenue;
determine one or more of the best stored ads based on the predicted impression revenue and an observed effective impression revenue of the stored ads, wherein the processor is programmed to track a past number of impressions and resulting actions, to estimate the observed effective impression revenue of the stored ads; and
wherein the processor is programmed to apply a blending function B to the predicted impression revenue p, and to the number of impressions i and number of resulting actions a;
B(p,i,a)wherein for each impression i and the resulting action a, the observed effective impression revenue of the stored ads is tested for statistical significance against the predicted effective impression revenue p, wherein when the statistical significance exceeds a predetermined threshold, the processor is programmed to use the observed effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads;
wherein when the statistical significance equals or is below a said predetermined threshold, then the processor is programmed to use the predicted effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads; and
transmit one or more of the automatically determined best stored ads to the user terminal for integration with the publisher page to be displayed; and
wherein if the processor determines that the analyzed publishing content is not ready for matching to the stored ads, the processor is programmed to transmit an ad of a determined general relevance to the user terminal for integration with the publisher page to be displayed, wherein the processor is programmed to determine general relevance based upon any of publisher selection or system analysis.
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Abstract
The system provides an automatically targeted network for text and graphical advertising based on cost-per-action bidded pricing, wherein actions comprise any of acquisitions, purchases, downloads, registrations, donations, clicks, and impressions. Contextual, search and behavioral relevance features are integrated to optimize ad selection for advertisers, who enter action objectives, associated bids, and creatives or catalog assets. The assets are automatically analyzed and stored, and ads are automatically constructed for catalog assets. When an ad request is received from a user terminal in regard to a publisher asset, e.g. a web page, the ad request is matched to a stored contextual analysis of at least a portion the publisher asset if available, and preferably to a profile associated with the user of the user terminal. The best advertisements are determined, based upon a predicted response, and are then served, i.e. displayed, at the user terminal, based upon available ad space.
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Citations
57 Claims
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1. A system implemented across a network having one or more publishing sites correspondingly associated with at least one publishing entity, each of the publishing sites comprising at least one publisher page having publishing content that is displayable to any user of the publishing site, and at least one available ad space, the system comprising:
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at least one processor programmed for; storing a plurality of anonymous profiles that are associated with a plurality of users; analyzing the displayable publishing content accessed from the publishing sites; storing the results of the analysis of the accessed publishing content; receiving from one or more advertising entities across the network and storing; one or more selectable action objectives associated with one or more advertising sites correspondingly associated with the advertising entities, and one or more ads having selectable links from which each of the respective advertising sites can be accessed; analyzing advertising content accessed from one or more of the advertising sites, wherein the advertising content comprises at least the ads received from the advertising entities; receiving from a user terminal across the network an automated request for one or more ads associated with a display to a user associated with the user terminal of one of the publisher pages at the user terminal, the publisher page to be displayed comprising the displayable publishing content and one or more of the available ad spaces; and determining if the analyzed publishing content is ready for matching to the stored ads; wherein if the processor determines that the analyzed publishing content is ready for matching to the stored ads, the processor is programmed to match the automated ad request to at least a portion of the analyzed publishing content for the publisher page to be displayed; statistically match the user to one of the stored plurality of anonymous profiles, using known information associated with the user, wherein the known information comprises any of location, gender, age, interests, purchases, usage patterns, or other prior actions by the user; predict a response to the ads by the user, wherein the prediction is at least partially based on the matched stored profile and any of the analyzed publishing content and the analyzed ads received from the advertising entities, and wherein said prediction comprises a predicted impression revenue; determine one or more of the best stored ads based on the predicted impression revenue and an observed effective impression revenue of the stored ads, wherein the processor is programmed to track a past number of impressions and resulting actions, to estimate the observed effective impression revenue of the stored ads; and
wherein the processor is programmed to apply a blending function B to the predicted impression revenue p, and to the number of impressions i and number of resulting actions a;
B(p,i,a)wherein for each impression i and the resulting action a, the observed effective impression revenue of the stored ads is tested for statistical significance against the predicted effective impression revenue p, wherein when the statistical significance exceeds a predetermined threshold, the processor is programmed to use the observed effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads;
wherein when the statistical significance equals or is below a said predetermined threshold, then the processor is programmed to use the predicted effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads; andtransmit one or more of the automatically determined best stored ads to the user terminal for integration with the publisher page to be displayed; and wherein if the processor determines that the analyzed publishing content is not ready for matching to the stored ads, the processor is programmed to transmit an ad of a determined general relevance to the user terminal for integration with the publisher page to be displayed, wherein the processor is programmed to determine general relevance based upon any of publisher selection or system analysis. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. A process implemented across a network having one or more publishing sites correspondingly associated with at least one publishing entity, each of the publishing sites comprising at least one publisher page having publishing content that is displayable to any user of the publishing site, and at least one available ad space, the process comprising:
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providing at least one processor that is programmed to perform the steps of; storing a plurality of anonymous profiles that are associated with a plurality of users; analyzing the displayable publishing content; storing the analysis of the publishing content; receiving one or more selectable objectives associated with one or more network sites from one or more advertiser entities; receiving a bid price correspondingly associated with each of the selectable action objectives assigned by the respective advertiser entities; receiving and storing one or more ads associated with the network site from the respective advertiser entities; analyzing the ads received from the advertiser entities; receiving from a user terminal across the network an automated ad request for one or more ads associated with a display to a user of one of the publisher pages at the user terminal, the publisher page to be displayed comprising the displayable publishing content and one or more of the available ad spaces; and determining if the analyzed publishing content is ready for matching to the stored ads; wherein if the processor determines that the analyzed publishing content is ready for matching to the stored ads, the processor performs the steps of; matching the automated ad request to at least a portion of analyzed publishing content for the publisher page to be displayed; statistically matching the user to one of the stored plurality of anonymous profiles, using known information associated with the user, wherein the known information comprises any of location, gender, age, interests, purchases, usage patterns, or other prior actions by the user; predicting a response to the ads by the user, wherein the prediction is at least partially based on the matched stored profile and any of the analyzed publishing content and the analyzed advertising ads received from the advertising entities, and wherein said prediction comprises a predicted impression revenue; determining one or more of the best stored ads based on the predicted impression revenue and an observed effective impression revenue of the stored ads, wherein the processor is programmed to track a past number of impressions and resulting actions to estimate the observed effective impression revenue of the stored ads; and
wherein the processor is programmed to apply a blending function B to the predicted impression revenue p, and to the number of impressions i and number of resulting actions a;
B(p,i,a)wherein for each impression i and the resulting action a, the observed effective impression revenue of the stored ads is tested for statistical significance against the predicted effective impression revenue p, wherein when the statistical significance exceeds a predetermined threshold, the processor is programmed to use the observed effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads;
wherein when the statistical significance equals or is below said predetermined threshold, then the processor is programmed to use the predicted effective impression revenue of the stored ads; andsending one or more of the determined stored ads to the user terminal or integration with the publisher page to be displayed; and wherein the processor performs the step of transmitting an ad of a determined general relevance to the user terminal for integration with the publisher page to be displayed if the analyzed publishing content is not ready, wherein the processor performs the step of determining general relevance based upon any of publisher selection or system analysis. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42)
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43. A process implemented across a network having one or more publishing sites correspondingly associated with at least one publishing entity, each of the publishing sites comprising at least one publisher page having publishing content that is displayable to any user of the publishing site, and at least one available ad space, the process comprising:
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providing at least one processor that is programmed to perform the steps of; storing a plurality of anonymous profiles that are associated with a plurality of users; analyzing the displayable publishing content; storing the analysis of the publishing content; receiving one or more selectable objectives associated with an advertiser campaign from an advertiser entity, the advertiser campaign comprising a plurality of assets, one of the assets comprising a network site and one or more ads; receiving a bid price correspondingly associated with each of the selectable objectives assigned by the advertiser entity; receiving and storing one or more of the ads associated with the advertiser campaign from the advertiser entity; analyzing at least a portion of the ads that were received from the advertiser entity; receiving from a user terminal across the network an automated ad request for one or more ads associated with a display to a user of one of the publisher pages at the user terminal, the publisher page to be displayed comprising the displayable publishing content and one or more of the available ad spaces; and determining if the analyzed publishing content is ready for matching to the stored ads; wherein if the processor determines that the analyzed publishing content is ready for matching to the stored ads, the processor performs the steps of; matching the automated ad request to at least a portion of the contextually analyzed publishing content for the publisher page to be displayed; statistically matching the user to one of the stored plurality of anonymous profiles, using known information associated with the user, wherein the known information comprises any of location, gender, age, interests, purchases, usage patterns, or other prior actions by the user; predicting a response to the ads by the user, wherein the prediction is at least partially based on the matched stored profile and any of the analyzed publishing content and the analyzed advertising content of the associated ads and the analyzed ads received from the advertising entities, and wherein said prediction comprises a predicted impression revenue; ranking one or more of the stored ads based on the predicted impression revenue and an observed effective impression revenue of the stored ads, wherein the processor is programmed to track a past number of impressions and resulting actions to estimate the observed effective impression revenue of the stored ads; and
wherein the processor is programmed to apply a blending function B to the predicted impression revenue p, and to the number of impressions i and number of resulting actions a;
B(p,i,a)wherein for each impression i and the resulting action a, the observed effective impression revenue of the stored ads is are tested for statistical significance against the predicted effective impression revenue p, wherein when the statistical significance exceeds a predetermined threshold, the processor is programmed to use the observed effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads;
if wherein when the statistical significance equals or is below a said predetermined threshold, then the processor is programmed to use the predicted effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads; andsending one or more of the ranked ads to the user terminal for integration with the publisher page to be displayed; and wherein the processor performs the step of sending an ad having a determined general relevance to the user terminal for integration with the publisher page to be displayed if the analyzed publishing content is not ready, wherein the processor performs the step of determining general relevance based upon any of selection by a publisher associated with the publishing site, or by system analysis.
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44. A process implemented across a network having one or more publishing sites correspondingly associated with at least one publishing entity, each of the publishing sites comprising at least one publisher page having publishing content that is displayable to any user of the publishing site, and at least one available ad space, the process comprising:
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providing at least one processor that is programmed to perform the steps of; storing a plurality of anonymous profiles that are associated with a plurality of users; receiving a catalog file from an advertiser entity across the network, the catalog file comprising a plurality of asset records, wherein each of the asset records comprises a plurality of fields correspondingly associated with an asset; receiving from the advertiser entity one or more action objectives associated with the assets; assigning bids for the received action objectives associated with the assets, wherein the assigned bids correspond to a price corresponding to an accomplishment of a corresponding action objective; analyzing one or more of the fields that correspond to each of the asset records; storing the analyzed asset records; automatically producing ads corresponding to the analyzed asset records, wherein the produced ads include the analyzed fields; statistically matching a user at a user terminal with one of the stored plurality of anonymous profiles, wherein the matching is at least partially based upon known information about the user, wherein the known information comprises any of location, gender, age, interests, purchases, usage patterns, or other prior actions by the user; predicting a response to the ads by the user, wherein the prediction is at least partially based on the matched stored profile and at least one of the analyzed fields associated with the automatically produced ads and any of the analyzed publishing content and the analyzed ads received from the advertising entities, and wherein said prediction comprises a predicted impression revenue; determining one or more of the best stored ads based on the predicted impression revenue and an observed effective impression revenue of the stored ads, wherein the processor is programmed to track a past number of impressions and resulting actions and to estimate the observed effective impression revenue of the stored ads; and
wherein the processor is programmed to apply a blending function B to the predicted impression revenue p, and to the number of impressions i and number of resulting actions a;
B(p,i,a)wherein for each impression i and the resulting action a, the observed effective impression revenue of the stored ads is are tested for statistical significance against the predicted effective impression revenue p, wherein when the statistical significance exceeds a predetermined threshold, the processor is programmed to use the observed effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads;
otherwise, the processor is programmed to use the predicted effective impression revenue of the stored ads; andsending one or more of the automatically produced ads for presentation to the user, based upon the prediction. - View Dependent Claims (45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57)
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Specification