Systems and methods for retrieving, in a first application using one or more processors, a user profile in which the user profile includes a user ID, and the first application includes a first application interface. The systems and methods further include detecting user selection, in the first application interface, of a sync command to a second application, in which the second application includes an executable script associated with the user ID, retrieving the executable script in response to the detecting the user selection of the sync command, integrating the executable script into an HTML interface associated with the user profile, and generating a two-dimensional graphical component in response to the integration of the executable script.

An improved architecture including system and methods for online advertising placement that provide possibly defaulting advertisement tags the opportunity to serve an advertisement ahead of a lower value tag that is guaranteed to fill, resulting in higher CPMs (i.e., Cost Per Mille) for web publishers. The system and methods are configured to deterministically render an advertisement impression from a list of possibly defaulting advertisements in a JavaScript-enabled web browser. The knowledge of the complete outcome of such an “ad chain” at render-time significantly reduces complexity and latency in the supporting ad server. The system and method centers around a novel JavaScript approach to detect when an advertisement has been loaded but not defaulted. Additionally, the system and methods integrate the network and RTB demand channels by looking at all demand sources simultaneously and selecting the buyer from within the user's browser, and address predictive pricing to further enhance the online advertising placement process.

A system for processing images captured in a retail store and automatically identifying misplaced products is provided. The system may comprise at least one processor configured to receive one or more images captured by one or more image sensors from an environment of a retail store, detect in the one or more images a first product, determine that the first product is not located in the first correct display location, cause an issuance of a user-notification associated with the first product, detect in the one or more images a second product, determine that the second product is not located in the second correct display location, and after determining that the second product is not located in the second correct display location and when the second urgency level is lower than the first urgency level, withhold issuance of a user-notification associated with the second product.

Methods, systems, and media for review content traffic are provided. In accordance with some embodiments of the present invention, a method, implemented on a processor, for reviewing advertisement placement on webpages is provided. The method can include: receiving a plurality of uniform resource locators (URLs) relating to the placement of a plurality of advertisements associated with an advertiser; obtaining, for the plurality of URLs, a plurality of images and a plurality of advertisement traffic and rating information relating to each of the plurality of URLs, wherein each of the plurality of images shows the placement of an advertisement on the page accessed by a URL; presenting a traffic display that includes the plurality of images for the plurality of pages, wherein the plurality of images are user selectable; and, in response to selecting one of the plurality of images, presenting the advertiser with the advertisement traffic and rating information for a URL corresponding to the selected image and providing the advertiser with an opportunity to provide feedback information for the rating information associated with the URL.

A self-consistent inception architecture includes a process that integrates online data and offline data to determine an estimated lift (“prior lift”) in the number of unique visitors (UVs) to a website caused by a television (TV) spot airing on an offline medium. The prior lift is used to adjust a UV profile of the website. A baseline thus produced is fitted through an inception process in which a locally weighted scatterplot smoothing algorithm is applied iteratively until a final baseline converges. The baseline from the inception process is used to determine a calculated lift. If the prior lift and the calculated lift are not consistent (e.g., within a threshold), the process is run iteratively until the prior lift and the calculated lift are consistent. The calculated lifts can be used to determine and visualize performance metric(s) relating to media creatives such as TV spots airing in the physical world.

A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values for each element of the collection of elements. The method further comprises specifying, in a sketch-frequency table, a set of discrete statistical values associated with the hash values and, for each discrete statistical value of the set of discrete statistical values, information indicative of a frequency at which binary representations of the hash values are associated with the discrete statistical value. The cardinality of the collection of elements is estimated based on the sketch-frequency table.

Embodiments are provided that facilitate launching of particular application program(s) determined as associated with an installed state on a mobile computing device without causing execution of such application program(s) or otherwise negatively impacting the performance of such application program(s). Example embodiments of the present disclosure are configured to, via a promotion application executed on a mobile computing device: receive user input selecting a first impression associated with a separate application program comprising a first additional application program separate from the promotion application program; programmatically initiate detection of an installation state associated with the separate application program; determine the installation state indicates the separate application program is installed; and in response to determining the installation state indicates the separate application program is installed, automatically initiate launch of the separate application program on the mobile computing device to cause rendering of determined information corresponding to the first impression.

A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values associated with the elements. The hash values specify bit positions within an array of bits. Hash values output from the hash logic conform to a geometric distribution such that bit positions of the array of bits corresponding to lower orders bits are more likely to be generated than bit positions corresponding to higher-order bits. Bits of the array of bits corresponding to the bit positions are set. The number of bits of the array of bits that are set is counted. Estimation logic estimates the number of unique elements of the collection of elements as a function of the number of bits of the array of bits that are set.

A system and methods are disclosed for scoring audience responsiveness or exposure to viewing of paid content or advertising via connected television devices (“CTV”) and/or over-the-top (“OTT”) delivery mechanisms. The scoring system and method determines relevant data and creates and records the relevant data in an “Ad Exposure File” and an “Advertiser Outcome File” and at regular intervals compares them to identify matches via overlapping combinations of IP Address/DID, Timestamp (for confirmation of appropriate recency) and recording a conversion event to the “Exposed Household Record.” of the appropriate household on the Ad Exposure File.

A non-transitory computer-readable recording medium stores therein a prediction program that causes a computer to execute a process including obtaining a machine learning model trained by using training data, the machine learning model predicting presence or absence of purchase actions or predetermined actions of users corresponding to feature information on the users, the training data including feature information on users and information indicating the presence or the absence of the purchase actions of commercial products or the predetermined actions, receiving input of a budget amount in an entry field displayed on a display in association with a user group including users including a common feature in the feature information, and displaying, in association with the budget amount on the display, feature information on the users included in the user group corresponding to the entry field.