The present disclosure optimally determines a contact between a user and an advertisement. An advertisement contact determination system according to one aspect of the present disclosure includes a communication unit configured to obtain position information of a device, and a control unit configured to determine that a user of the device has come into contact with an Out Of Home (OOH) advertisement if the OOH advertisement is included in a certain range in a traveling direction of the user based on the position information of the device. The communication unit obtains a log of a certain apparatus, and the control unit determines whether the device exists in vicinity of the certain apparatus in a certain period of time or not and, if the device exists, associates the log of the certain apparatus in the certain period of time with the device.

Methods and apparatus for determining a unique audience exposed to media while reducing memory resources of a computing device are disclosed herein. An example apparatus includes memory; instructions in the apparatus; and processor circuitry to execute the instruction to, based on impression requests from a plurality of client devices via a network, log a plurality of impressions corresponding to media accessed at the client devices; generate a product by multiplying a count of the impressions by a square of a count of registered users of a database proprietor exposed to the media; generate a quotient by dividing the product by a count of demographic impressions logged by the database proprietor; and determine a unique audience size based on a square root of the quotient.

A method and apparatus for providing Web advertisements to online users is disclosed. A balanced set of negative data points and positive data points is derived from a log of Ad impressions and used to train a classifier. In response to an Ad request signal, a plurality of Ads is retrieved from a database. The Ad request signal indicates a request to provide an Ad for a slot available on a Web page associated with a website. The signal is provided in relation to an access of the Web page by an online user and includes information related to the online user. A choice of an Ad is predicted based on the information related to the online user and the plurality of Ads. The Ad is provided to a Web server to cause display of the Ad on the slot when the Web page is displayed to the online user.

Systems and methods for filtering data representative of consumers targeted for marketing campaigns that include receiving, at a first computer system operating on behalf of a payment card network, a first data set comprising pseudonymized data of a plurality of consumers derived from respective consumer files, the pseudonymized data of each consumer including a unique artificial identifier for the consumer, the first data set being received from a second, independent computer system storing keys configured to re-identify at least some of the pseudonymized data of the first data set; comparing, at the first computer system, the pseudonymized data of each of the consumers with payment card network criteria to generate a second data set comprising a subset of the first data set corresponding to a qualifying subset of the consumers and unique artificial identifiers included in the first data set; and transmitting the second data set from the first computer system to the second computer system.

Aspects of the present disclosure involve a system and a method for performing operations comprising: receiving, by a messaging application, content from a given user; selecting a metric for measuring performance of the content on the messaging application; measuring performance of the content on the messaging application; computing a value of the performance of the content on the messaging application based on the selected metric; and updating a restricted use token wallet stored in a profile for the given user based on the computed value of the performance of the content.

This specification describes technologies relating to content presentation. In general, one aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving ad information from a seller; generating, using one or more processors, a single conversion ad using the received ad information, where the single conversion ad has an available inventory of one such that only a single conversion of the ad can be performed; transmitting the single conversion ad to one or more potential buyers; receive an input from one of the one or more potential buyers; and notifying the seller of the user input. Other embodiments of this aspect include corresponding systems, apparatus, and computer program products.

A method to create advertisement and sales trackability is provided. The method includes collecting a consumer data and retrieving, from a publishing server, a media data linking an audience with a content provided by the publishing server, the content including an advertisement for a product, and retrieving a retailer data indicative of a purchase track record of the product. The method also includes identifying one or more attributes of a population segment associated with the consumer data, the media data, and the retailer data, determining an adjustment factor indicative of a statistical data associated with the population segment, and generating, based on the adjustment factor, a measurement scheme to support a decision to modify, improve, or cancel a campaign. A system and a non-transitory, computer-readable medium storing instructions to perform the above method are also provided.

A system and method for quantifying impact of script error exceptions on performance of an online retail platform. A method includes selecting at least one performance metric for a webpage, wherein the selected performance metric has an impact due to at least one script error exception encountered on the webpage visited by a first user device; retrieving a normal value for each of the at least one selected performance metric for the webpage visited by a second user device; retrieving an abnormal value for each of the at least one selected performance metric for the webpage visited by the second user device; comparing the abnormal value to the normal value of a respective selected performance metric; and determining a performance impact score based on the comparison, wherein the performance impact score is indicative of a reduction in a performance metric of each of the least one selected performance metric.

Described are systems and methods to determine advertisements to be presented to a user. To determine the advertisements to be presented to the user, the described systems and methods utilize localized contextual information to select the advertisements and the relative positioning of the advertisements to be presented, so as to select and present more relevant advertisements based on the content that is surrounding and proximate to the presentation of the selected advertisements.

Various methods, apparatuses/systems, and media for automating sponsored-search data pipelines are disclosed. A processor generates keyword-level metrics data based on received bidder input data that includes cost-per-acquisition (CPA) data and total spending data for each keyword; determines campaign-level CPA threshold data chosen at previous iteration of search campaign and a target CPA data used for current search campaign; calculates, campaign-level metrics data that includes the CPA data and adjusted total spending data; quantifies a final campaign-level reward data based on the calculated campaign-level metrics data, adjusted total spending data, and the target CPA data; updates a distribution corresponding to CPA-threshold data chosen at previous iteration using the final campaign-level reward data; samples CPA-threshold distributions and determines CPA-threshold data chosen at current iteration; executes campaign-level heuristics using the keyword-level metrics data, campaign-level metrics data, and the CPA-threshold data chosen at current iteration; and displaying final heuristic-execution data onto a GUI.