The Power Buy System includes a computer based platform wherein sellers and buyers log into a website having a pre-configured Power Deal listing on an item. The pre-configured Power Deal listing may set forth one or more tier pricing based on quantity. The pre-configured Power Deal or the new Power Deal may be activated upon commitment from a first buyer. The buyer is provided tools to encourage other social media contacts to purchase an item in order to aggregate a larger buyer collective and sellers are allowed to offer a lower price than what is stated in the buy now price to further encourage additional buyers participation so that more items may be sold.

A method and system for placement of graphical objects on a page to optimize the occurrence of an event associated with such objects. The graphical objects might include, for instance, advertisements on a webpage, and the event would include a user clicking on that ad. The page includes positions for receipt of the object material. Data regarding the past performance of the objects is stored and updated as new data is received. A user requests a page from a server associated with system. The server uses the performance data to derive a prioritized arrangement of the objects on the page. The objects are arranged according to a calculation and returned to the user on the requested page.

A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. The sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. The first or second activity information can include a cookie, which can be used to identify a node in a social graph as being representative of a particular person or user. When a match is not found, a fingerprinting approach can be performed using attributes, such as device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, or behavioral patterns.

Systems and methods for predicting an outcome for a marketing asset. The systems and methods comprise first determining by a computing device, for a marketing asset received by the computing device, at least one asset type of the marketing asset. The marketing asset is parsed, by the computing device, into a plurality of segmented components, based on the determined at least one asset type. For at least one of the plurality of segmented components, at least one discrete marketing message conveyed by the marketing asset is determined, by applying at least one of a predictive model or rules to the at least one segmented component, where the at least one predictive model or rules are stored in a memory associated with the computing device. The method further includes determining, for each of the at least one discrete marketing message, at least one associated score. The method yet further includes inputting the determined at least one associated score to a trained predictive model to obtain a predicted marketing outcome, where the trained predictive model was trained using training scores associated with a multitude of training discrete marketing messages as independent variables and corresponding training marketing outcome data as dependent variables.

An apparatus, method and recording medium for providing an advertisement are disclosed. The apparatus receives, from an advertiser terminal apparatus, registration of a product to be advertised, an allowable budget, and an advertising period, and sets a charging unit price per customer group as to the registered product. The apparatus transmits the charging unit price per customer group to the advertiser terminal apparatus and then receives a selection of a target customer group and a charging unit price from the advertiser terminal apparatus. Also, the apparatus calculates an advertisement exposure frequency, based on the selected charging unit price, the registered allowable budget, and the registered advertising period, and then provides an advertisement for the registered product to a user terminal apparatus of the target customer group, based on the advertisement exposure frequency.

Embodiments of the invention relate to computer-implemented methods and systems for managing and analyzing subscriber history data present within a service provider infrastructure. The subscriber history data is free of personally identifiable information and is aggregated according to an anonymous attribute. A predictive model is used to rank a plurality of individuals or households according to one or more household attributes, such as media habits and/or media exposure. Advertisers are provided with access to the ranked data, such that the advertisers can improve marketing metrics for advertisements delivered to the households. Service providers may receive monetary compensation for providing access to the ranked data.

The present disclosure is directed toward systems, methods, and non-transitory computer readable media that dynamically modify content distribution campaigns based on triggering conditions and actions. In particular, systems described herein can provide a user interface for display to a publisher device that includes a plurality of selectable options for setting triggering conditions and/or actions. For example, the disclosed systems can utilize a machine learning model to generate suggested triggering conditions and/or actions for one or more content distribution campaigns of a provider. Moreover, the disclosed systems can generate custom rules based on selected triggering conditions and actions and apply the custom rules during execution of digital content campaigns. For instance, the disclosed systems can monitor performance of content campaigns, detect triggering conditions, and dynamically modify digital content campaigns based on actions corresponding to the triggering conditions.

Inventory data is stored, wherein the inventory data represents for each of a plurality of broadcast stations a corresponding inventory of audio advertising spots available from that broadcast station to be filled by an advertising placement system. An advertising campaign data representing a set of advertising objectives of an advertising campaign is received. The inventory data is used to iteratively select advertising spots to be associated with the advertising campaign, based at least in part on a respective computed fitness of match between each selected advertising spot and said advertising objectives.

A system that incorporates teachings of the subject disclosure may include, for example, determining identified impressions that are detected from consumption data collected from a group of media processors where the identified impressions represent viewing of selected content and where the consumption data indicates channel tuning events at the group of media processors including changing of channels, applying a ridge regression analysis to the identified impressions to determine a predicted number of target impressions per advertisement slot, and generating a media plan based on a ratio of an advertisement slot cost to the predicted number of target impressions per advertisement slot. Other embodiments are disclosed.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for reducing bias caused by cleared cookies. In one aspect, a method includes obtaining, from a historical data store storing data obtained from cookies that have been placed on various client devices, a set of the data obtained from the cookies. The contents of a given cookie are used to identify an initialization time when the given cookie was placed on a given client device by a server. A determination is made, based on the initialization time, that the cookie has an age that is less than the threshold age. Data obtained from the given cookie is filtered from inclusion in a final set of data that is used to generate measurements based on the age of the cookie being less than the threshold age.