Systems and methods for verifying an advertisement impression in a digital environment are provided. In some aspects, methods of the subject technology include operations for defining a portion of the digital environment as an impression area, wherein the impression area is associated with a tagged advertisement area, providing a stream of an advertisement to the tagged advertisement area, and updating advertising impression information stored in memory regarding the advertisement, wherein an advertising impression is based on the identification of the character within the impression area and the availability of an unobstructed line-of-sight between the character and the tagged advertisement area. In some aspects, computer readable media are also provided.

Systems and methods are provided for determining a quantity of network location visitors that are likely generated or encouraged by specific offline events. A corresponding number of leads may then be attributed to and associated with those specific events. Ongoing conversion activity of those visitors may be tracked and associated with the offline events. Conversions of those visitors may be attributed entirely or partially to one or more specific offline events. The effectiveness of each offline may then be evaluated based on aggregate lead and conversion information.

A computer-implemented method is disclosed for processing metrics via a controller. The controller comprises a processor and a memory storing program instructions which when executed by the processor causes implementation of the steps of generating or receiving metrics characterising digital traffic and/or related user behaviour from one or more sources and generating or receiving a tabular dataset associated with the metrics, wherein the dataset comprises rows of metrics and dimensions in which each row represents a subset of a metric grouping characterised by a combination of dimensions. The processor further implements the steps of receiving one or more partition identifiers representing a data structure of dataset partitions, assigning one or more metric groupings to one or more partition identifiers and analysing the dataset according to partition identifiers.

An advertisement is delivered based on a first limiting element, a specified number of selections, and an expected selection rate. Based on an expected number of selections and an actual number of selections of the advertisement before the end of a counting period, the number of selections to be further needed at the end of the counting period is estimated. For each of a plurality of second limiting elements different from the first limiting element, an actual selection rate of the advertisement by a group, among the recipients of the advertisement, limited by the second limiting element is obtained. Based on the actual selection rates, a limiting element to be added to delivery requirements from among the plurality of second limiting elements is determined. Based on the determined limiting element, the corresponding actual selection rate, and the estimated number of selections, additional recipients of the advertisement are determined.

The systems and methods described herein attempt to capture the impact on both the promoted items and other related products. The systems and methods analyze attached sales impact only for items that are more likely to be purchased with the featured product. The systems and methods also allow for measuring a cannibalization impact by analyzing the impact on potential cannibalized products and items that are more likely to be purchased with the cannibalized products. By aggregating the promoted impact and cannibalized impact, including the items with strong co-selling relationships, a full picture of the promotion can be obtained. Further, combining the item-level results into custom groupings can allow for further business insights.

Systems and methods of correlating an online content interaction with an offline content interaction are provided. A data processing system can identify an online conversion by a first computing device of a content item associated with a content provider, provide an online conversion identifier to an offline conversion identification unit, receive from the offline conversion identification unit detection data indicating that the offline conversion identification unit has detected the online conversion identifier on one of the first computing device and a second computing device, and provide the detection data to a content provider computing device associated with the content provider.

Detecting and managing fraud in an online system is described. An example computer-implemented method can include obtaining a plurality of signals. Each of the signals may be purported to have been generated by a different client device. The method also includes calculating a summary value for the obtained signals that indicates a measure of similarity between the obtained signals and an expected distribution of signals. The method also includes determining that the summary value represents a statistically significant deviation of the obtained signals from the expected distribution of signals. The method also includes labeling the obtained signals as fraudulently generated based on the statistically significant deviation.

Apparatuses, methods, and storage media for determining effectiveness of an advertisement are described. In one instance, an apparatus for determining effectiveness of an advertisement may include a digital device matching engine, communicatively coupled to the processors, to receive and process information obtained from a web site accessed by a digital device, and to match the digital device to a TV set, based at least in part on the processed information. The apparatus may further include a conversion determination engine, communicatively coupled to the processors, to determine a level of conversion associated with an advertisement rendered by a broadcasting media to the TV set, based at least in part on the matching of the digital device to the TV set. The apparatus may be configured to provide recommendations to advertisement regarding the effectiveness of their advertising campaign. Other embodiments may be described and claimed.

This disclosure generally covers systems and methods that schedule posts of one or more images, videos, or other digital content items through an account of a social networking system in a way that optimizes user engagement. In particular, certain embodiments of the disclosed systems and methods determine when to post digital content items by calculating data-driven user engagement scores and updating those scores with data tracked by the social networking system.

A method and system for generating concept structures and taxonomies based on received multimedia data elements (MMDEs) are provided. The method comprises receiving at least one MMDE; generating at least one signature for the at least one received MMDE; matching the at least one generated signature to a plurality of clusters to find at least one matching cluster; associating the at least one generated signature with each of the at least one matching cluster; and analyzing the at least one generated signature with respect to a signature reduced cluster (SRC) of each of the at least one matching cluster to generate a taxonomy, wherein the taxonomy relates to the at least one received MMDE and an MMDE respective of each of the at least one matching cluster.