A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include engaging a user in a primary activity; the primary activity may include a plurality of stages. The operations may include compiling at least one risk-reward score for an advertisement placement of an advertisement for at least one of the plurality of stages. The operations may include updating, dynamically, the at least one risk-reward score and identifying a recommended stage for the at least one advertisement; the recommended stage may be based on the risk-reward score. The operations may include displaying the at least one advertisement to the user at the recommended stage.

A system may determine a field of view of a structure; identify a set of road segments that fall within the view area of the advertising unit; and identify mobile devices that have been physically located at locations associated with the road segments within the field of view (e.g., located within vehicles that have traversed the road segments). The system may further receive a request for a report that indicates a quantity or other information (e.g., demographics information) regarding the identified mobile devices over a period of time.

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.

Described herein are systems and methods for associating consumer-perceived broadcasted content with consumer actions. In some embodiments, a computer-based memory communicatively coupled to a processor has computer executable instructions stored therein capable of implementing various components, including a definition component configured to define one or more targeted content features, such as a specific television commercial. These embodiments can further comprise a recognition component configured to recognize when the targeted content features are broadcast through a media device in a particular household and an airing database component configured to store airing information regarding the broadcast. In some embodiments, Automatic Content Recognition is utilized, allowing offline consumer perception of an advertisement to be attributed to online activity of a consumer. In some embodiments, the airing information can be associated with an internet protocol (IP) address and can be correlated to a corresponding IP address associated with online consumer action.

A method and a web server store a plurality of web page elements that may be rendered on a browser of a user computing device to display a web page. The web page includes a first ad space for displaying an ad that is visible to the user and a second ad space for displaying an ad that is not visible to the user. A first ad request for the first ad space and a second ad request for the second ad space are received and associated with a first ad campaign and a second ad campaign, respectively. A first ad from the first ad campaign is provided to the user computing device so that the first ad is visible to the user, and a second ad from the second ad campaign is provided to the user computing device so that the second ad is not visible to the user.

Methods and apparatus are disclosed to monitor impressions of social media messages. An example method includes receiving at a server a request for media, the request addressed to a uniform resource locator, the request corresponding to a social media message to be presented with the media, and the request including a user identifier. The method also includes crediting the social media message with an impression based on the request being addressed to the uniform resource locator. The method also includes identifying that the impression corresponds to an original intended recipient of the social media message based on the user identifier matching a second user identifier stored in a list of subscribers that subscribe to receive messages from an original sender of the social media message.

Methods and apparatus to monitor media presentations are disclosed. Disclosed example apparatus include memory, instructions, and at least one processor to execute the instructions to at least receive demographic information from a user, transmit the demographic information to a central facility, cause storage of a consent identifier in a pasteboard of the media device, the consent identifier accessible to a first instrumented application and a second instrumented application executed in a sandbox environment, the consent identifier to indicate to the first instrumented application and the second instrumented application that monitoring is allowed, access the consent identifier from the pasteboard, present media, generate monitoring information if the consent identifier permits collection of monitoring information, not generate monitoring information if the consent identifier does not permit the collection of the monitoring information, and transmit the monitoring information to the central facility.

Techniques for programmatically interfacing with mobile chat sessions are discussed herein. Some embodiments may include one or more servers configured to: access the mobile chat session hosted by the mobile chat server; receive input chat data from the mobile chat server; determine promotions scores of candidate promotions based at least in part on the input chat data; and provide the output chat data to the mobile chat server including an electronic marketing communication of one or more promotions selected based on the promotion scores. The one or more servers may be further configured to programmatically interact with chat accounts within the mobile chat session, such as to request additional search terms for improved promotion relevance targeting, among other things.

Processor systems to estimate audience sizes and impression counts for different frequency intervals are disclosed. An example processor system includes a memory management unit (MMU) to assign requests from computing devices indicative of accesses to media to a first block of memory and to assign user-identified impression data corresponding to user-identified impressions to a second block of memory. The processor system including an arithmetic logic unit (ALU) to determine multipliers relating a first probability distribution for the user-identified impressions to a second probability distribution for census impressions. The multipliers based on probability constraints defined by weighted probabilities associated with the second probability distribution, where different ones of the probabilities weighted based on estimated populations for corresponding ones of the different demographics. The ALU to determine a plurality of census impression counts associated with the census impressions based on the multipliers.

Apparatus, systems, and methods to identify consumer content exposure are disclosed. An example apparatus includes at least one memory; machine readable instructions; and processor circuitry to at least one of instantiate or execute the machine readable instructions to detect a first exposure of a first consumer to a marketing campaign during a first time period; identify the first exposure as a first recency exposure; detect a second exposure of the first consumer to the marketing campaign during one of the first time period or a second time period; when the second exposure is detected during the first time period, identify the first time period as an iterative frequency exposure; and when the second exposure is detected during the second time period, identify the second exposure as a second recency exposure.