A system and method is provided for determining when an electronic correspondence is reviewed by a consumer, and referencing this information when generating a subsequent electronic correspondence. The information may be used to determine when to send the subsequent electronic correspondence to the consumer. For example, the subsequent correspondence may be sent at the same time of day as when the consumer is determined to have previously reviewed an electronic correspondence. The information may also be used to determine what to include in the subsequent electronic correspondence. For example, time-sensitive promotions that are selected based on the information identifying the previous time at which the consumer reviewed a previous electronic correspondence, may be included in the subsequent electronic correspondence.

A method can include sending a request to a media content provider requesting media content and receiving the media content and instructions from the media provider. The instructions can be utilized by the media provider to broadcast the media content. The media provider can store the received media content in a database process the instructions then distribute the media content and the instructions to distributed media outlets. The media content provider can receive information indicating that the media content was broadcast by the distributed media outlets according to the instructions.

Embodiments are provided that improve persona tracking and use to improve the accuracy of determinations and actions that rely on such persona(s). Some example embodiments track user information associated with a profile. Example embodiments further generate personas associated with the profile based on the user information. Example embodiments further receive time data and/or location data from a user device. Example embodiments further determine a selected persona based on the time data and/or the location data. Example embodiments further determine a preference dimension value based on the selected persona. Example embodiments further identify promotion data representing a plurality of promotions. Example embodiments further, for each promotion, generate a first dimension score corresponding to the preference dimension value based on the selected persona. Example embodiments further determine a ranking for the promotions based on the first dimension score for each promotion.

Among other things, videos and commercials are downloaded to a mobile device for storage on the mobile device and later playout on the mobile device. The downloading includes downloading of metadata associated with the commercials and based on which the mobile device can select commercials for insertion into videos being played back to the user of the mobile device. The commercials to be downloaded are selected based on one or a combination of any two or more of the location of the user, the type of mobile device, and personally-identifiable information about a user of the mobile device.

A service provider may receive item price information and/or point of sale (POS) transaction information from a plurality of merchant devices associated with a plurality of merchants. The service provider may categorize the plurality of merchants according to the types of items offered by the respective merchants, and may further categorize the merchants according to the locations at which they conduct business. The service provider may subsequently determine a price recommendation or other pricing information for a particular item offered by a particular merchant. A merchant device of the particular merchant may present the pricing information in a user interface that enables the merchant to view projected sales at various different price points. Further, the merchant may be able to specify one or more factors used for determining the recommend price, such as a desired business model, a desired clientele, a desired profit margin, or the like.

Aspects of the subject disclosure may include, for example, a method, operating at a processing system including a processor, can include receiving a reply message from a communication device responsive to a query signal and including audio information collected at a presentation area, determining consumer presence information at the presentation area according to the audio information collected at the presentation area, determining a probability of a consumer advertising experience according to the consumer presence information, selecting first advertising media from a set of advertising media according to the probability of consumer advertising engagement, and presenting the first advertising media to the presentation area via the presentation system. Other embodiments are disclosed.

Forecasted attributes may be determined for scheduled media items based at least in part on observed characteristics associated with previously presented media items. A division of the scheduled media items into a plurality of media segments may be identified based on the forecasted attributes. A media allocation plan may be determined by solving an optimization problem that includes the media segments and the forecasted attributes.

A podcast system and method are provided to select and deliver media ads over a network to a user device and to insert the media ads in media content subscribed to and delivered over the network to the user device.

A system and method for dynamically tracking and capturing content and displaying the content on public or semi-public non-personal digital displays. In exemplary embodiments, the content may include an urgent notification that is displayed within a slot of looped content with the manner in which the urgent notification is displayed depending on the level of urgency and attributes of the non-personal digital displays.

A system and method for implementing a one-stop advertising campaign through a non-digital advertising medium provides a single platform for an advertiser to implement an advertisement on a non-digital advertising medium. The advertiser, through a one-click functionality on the platform, selects the advertising medium, the advertising-related workers to implement the advertisement, the advertising costs, and the timeline for advertising on the advertising medium. One or more advertising-related workers upload skill sets and fees for the advertiser to review before selecting. The system generates recommendations of appropriate workers to implement the advertisement campaign based on needs of the advertiser. The system also integrates sensors and/or positioning systems into the advertising media to detect the numbers, physical features, relative position, and movement pattern of consumers in proximity to the advertising medium. This allows a processor and algorithms to generate consumer data useful to the advertiser for marketing and setting advertising costs.