The present disclosure relates to a telecommunication method for monitoring with a mobile end user telecommunication device a telecommunication process on a digital telecommunication system using a telecommunication process monitoring server. The telecommunication process monitoring server is connectable with the mobile end user telecommunication device via a mobile wireless cellular digital telecommunication network. The telecommunication process monitoring server further is connectable with a real-time database. The digital telecommunication system further comprising a plurality of second telecommunication devices being connectable with the telecommunication control server via one or more second digital telecommunication networks. The telecommunication process comprises sending one or more telecommunication messages to the plurality of second telecommunication devices. The real-time database is configured for receiving and storing a plurality of telecommunication status reports about the status of the processing of the one or more telecommunication messages by the telecommunication system.

Technologies for attributing purchases to a targeted marketing campaign include associating a captured payment card number and a captured cardholder identifier with a globally unique identifier. Additional payment card numbers related to the captured payment card number are associated with the globally unique identifier. A cardholder-specific marketing message associated with a targeted marketing campaign is transmitted to the captured cardholder identifier based on the globally unique identifier. The targeted marketing campaign is for an advertised product, which corresponds to a product identifier. A purchase transaction is attributed to the targeted marketing campaign in response to determining that a payment card number associated with the purchase transaction matches any of the payment card numbers associated with the globally unique identifier and determining that a product identifier corresponding to a purchased product of the purchase transaction is associated with the targeted marketing campaign. Other embodiments are described and claimed.

A wearable apparatus and method are provided for capturing image data. In one implementation, a wearable apparatus for capturing image data is provided. The wearable apparatus includes at least one image sensor for capturing image data of an environment of a user, wherein a field of view of the image sensor includes a chin of the user. The wearable apparatus includes two or more microphones, and an attachment mechanism configured to enable the image sensor and microphones to be worn by the user. The wearable apparatus includes a processing device programmed to capture at least one image, identify the chin of the user to obtain a location of the chin, select a microphone from the two or more microphones based on the location, process input from the selected microphone using a first processing scheme, and process input from a microphone that is not selected using a second processing scheme.

Various embodiments are described herein for methods and systems that can be used for optimizing Web traffic performance. In at least one embodiment, there is provided a method for optimizing Web traffic performance, where a buyer system hosts one or more websites and purchases Web traffic from one or more source platforms via a network. The method comprises storing a predetermined blacklist threshold in a memory corresponding to the buyer system; receiving a plurality of Web traffic visitors from a plurality of source platforms at a user interface module corresponding to the buyer system; recording, in the memory, a number of Web traffic visitors received by the buyer system; for each source platform, determining, at a processor corresponding to the buyer system, a number of actions performed by at least some Web traffic visitors received from the corresponding source platform; for each successive visitor, determining, at the processor, a score based on the number of Web traffic visitors and the number of actions performed by at least some Web traffic visitors received from the corresponding source platform, the score being determined in real-time or batch mode; and for each successive visitor, if the determined score is greater than the predetermined blacklist threshold, accepting the corresponding successive visitor by the buyer system.

Disclosed is a method that includes: profiling a set of mobile applications according to revenue-related parameters; tracking a user's interaction with a mobile application; scoring the user's interaction levels, and based on the score, grouping users into mobile analytics groups associated with the targeting profiles; facilitating the transmission of user information, user interaction data, and specific mobile analytics groups to advertising campaigns. The method may be executed on a digital device. A related system is disclosed.

In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers. In embodiments, predictive models based on gross revenue may be optimized using promotion category-dependent price boosting.

Systems and methods are disclosed for evaluating promotional campaigns. The system estimates a target conversion rate for an advertising campaign for a media asset and determines an actual conversion rate for the advertising campaign. The system, in response to determining that the target conversion rate and the actual conversion rate are similar, determines a target demographic audience for the target conversion rate. The system determines a primary demographic audience for the actual conversion rate and compares a first characteristic of the target demographic audience and a second characteristic of the primary demographic audience. Responsive to the determination that the target demographic audience and the primary demographic audience are different, the system generates for display a notification indicating that the target demographic audience and the primary demographic audience are different.

The present disclosure relates to a system and method to enhance user interaction experience with a data transport stream displayed as advertisements on a computing device. The method include the steps of receiving, a data transport stream having at least one uniquely identified token along with one or more clickable moments inserted in one or more elementary data stream components of a said data transport stream, by a computing device; displaying, on a user interface of the computing device, said data transport stream to one or more users, wherein said one or more clickable moments are displayed, in real-time, along with said data transport stream; and transmitting, by the computing device, in real-time, one or more user interactions of the users, responsive to clicking on the user interface by said users while said one or more clickable moments are being displayed, to one or more repositories.

To provide secure single-source panel audience measurement data while providing confidentiality and security of panel membership, an audience measurement server may capture content identifiers and client identifiers of devices receiving content. A panel provider may generate a probabilistic data structure via a hash of the client identifiers. The audience measurement server may utilize the filter array to extract a subset of measurement data including the data of the panel members, as well as data of some non-panel members as false positives, without being able to distinguish between the members and non-members. The audience measurement server may encrypt the extracted subset of data with each client identifier corresponding to an item of data as a key, and send the encrypted data to the panel provider, thus including both panel and some non-panel data, with the panel provider only able to decrypt data corresponding to its own panel members.

An advertising (ad) system allows users to specify a budget for an advertisement (ad) campaign including ad requests (ads), and the ad system automatically determines bids on a per-impression basis to pace the ad spend according to the budget. The ad system computes a regret metric for the ad campaign, which is the total amount over the course of the ad campaign that the advertiser had to pay for presenting an ad above the ideal bid (e.g., the bid that would have captured at least a threshold number of the lowest priced impressions during the ad campaign's life while spending the budget). The ad system may use the regret metric to indicate the performance of the ad campaign, e.g., as feedback for the advertiser.