A method including receiving data including an impression value and an attribution value for a list item in an advertising campaign is provided. The method includes correlating the data with multiple advertising attributes of the advertising campaign to identify a salient attribute for an expected result of the advertising campaign. The method also includes modifying the salient attribute in an advertisement payload for the list item and providing the advertisement payload including the salient attribute to a server in a network for distribution among users communicatively coupled to the network. A system and a non-transitory, computer-readable medium storing instructions to cause the system to perform the above method are also provided.

A method for auditing an advertisement impression in which a first advertisement was presented in conjunction with first media content is disclosed. The method generally comprises transmitting to a plurality of second computing devices a plurality of randomly generated first cryptographic proofs; receiving, a first message from a second computing device indicating that the first advertisement was presented in conjunction with the first media content; and evaluating the first targeting model for the first advertisement based on the at least one media content classifier.

An attention application measures a user's attention focused on publisher content and advertisements to create an attention metric. Attention can be measured via hardware sensors or by user interactions with input/output hardware. A user attention metric profile can be used to modify content, content presentation, and/or match ads. Aggregate attention metrics can be used by publishers or third parties. Attention consumers may reward attention with a digital asset. A proof-of-attention can be made based on secure attention sensor hardware and/or a zero-knowledge proof.

A computerized hub connects companies seeking marketing services and marketing companies that provide marketing services. The systems and methods first provide hub-based tools to allow the company to develop a high-level marketing plan in accordance with the company's type of business, industry, geographic location, and marketing budget. Tool are also provided to facilitate budgeting, selecting, planning, launching, and reporting. In embodiments, the hub will have APIs to allow customers to provide a link to the customer's scheduling and accounting software to help develop the marketing plan and to monitor the effectiveness of the plan. The hub provides also provides interfaces for receiving performance data from marketing companies so their services may be offered to marketing service purchasers. Once a marketing company is selected, it is provided with additional interfaces which specify the campaigns and tasks for which the marketing company is responsible to implement. The computerized also provides real-time marketing results based upon real-time sales and marketing data, and generates updated marketing campaigns based upon triggers applied to the real-time sales and marketing data.

In one embodiment, a method includes obtaining, from a demand-side platform (DSP), impression data specifying service providers and consumer tokens representing consumers who have received digital impressions of a set of advertising campaigns. A set of tokenized claims data records related to a prescription of a product is then received from a database server. A result set of integrated measurement records specifying measured campaigns linking the tokenized claims data records with impression data associated with consumer tokens and/or service provider identifiers is further received from the database server. Aggregated analytics reports based on the integrated measurement records are generated and presented. A machine learning model may be trained using a training dataset comprising features selected from the impression data and tokenized claims data records, to predict bid values or other parameters for use in updating, optimizing or modifying operation of the DSP for the original campaign or for other campaigns.

In one embodiment, a method includes obtaining, from a demand-side platform (DSP), impression data specifying service providers and consumer tokens representing consumers who have received digital impressions of a set of advertising campaigns. A set of tokenized claims data records related to a prescription of a product is then received from a database server. A result set of integrated measurement records specifying measured campaigns linking the tokenized claims data records with impression data associated with consumer tokens and/or service provider identifiers is further received from the database server. Aggregated analytics reports based on the integrated measurement records are generated and presented. A machine learning model may be trained using a training dataset comprising features selected from the impression data and tokenized claims data records, to predict bid values or other parameters for use in updating, optimizing or modifying operation of the DSP for the original campaign or for other campaigns.

A delayed grouping (batch) processing of previous campaign delivery pacing decisions and corresponding outcomes (deliveries) is used to configure a new auction experiment iteration. In the new iteration, a campaign that was previously over-delivered is classified as either (a) over-delivered due to incorrect pacing or (b) over-delivered due to auction experiment design. After the delayed processing, the new auction experiment iteration is conducted with a mitigating action taken on the previously over-delivered campaign if the campaign is classified as (b) over-delivered due to auction experiment design. For example, the mitigating action can include removing the campaign from a subsequent iteration of the experiment, or the experiment can be redesigned. By doing so, the over-delivery caused by the campaign due to the auction experiment design is avoided when performing the new auction experiment iteration.

A system for training a bidding model comprising: a plurality of tactics stored on at least one database; a plurality of hyperparameters; in response to an available inventory from a publisher relayed through a real time bid server, computing a bid on the available inventory; sending the bid to the real time bid server; receiving an auction result in response to the bid; calculating a plurality of rewards based on the auction result and the tactics; calculate a plurality of q values based on the rewards; calculate a plurality of losses; backpropogating the losses through the bidding model.

Generating a cannibalism score for a paid ad in a search engine results page (SERP) by gathering keywords relevant to an advertiser, defining rules that compute a cannibalism score for the ad in relation to a corresponding unpaid listing, where the cannibalism score estimates the reduction in revenue to the advertiser due to the ad appearing in the same SERP as the corresponding listing, providing a keyword to a search engine, receiving a SERP from the search engine, determining the position of a first ad placed by the advertiser from among one or more ads in the SERP, determining the position of a corresponding unpaid listing from among a plurality of unpaid listings in the SERP, and applying the rules to the ad and to the corresponding unpaid listing to obtain a cannibalism score for the ad.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: displaying content elements on one or more websites to users; tracking respective impression response data for each impression of a respective content element of the content elements comprising (a) a respective response of a respective user of the users and (b) a respective time of the respective response of the respective user; determining respective weightings of the content elements based on posterior distributions using the respective impression response data, as adjusted by a temporal decay factor, based on the respective times of the respective impression response data for the content elements; and generating a webpage of the one or more web sites to comprise a selected content element based on the respective weighting of the selected content element. Other embodiments are disclosed.