The subject personalized consumer advertising/ad placement system provides the ability for advertisers, ad agencies, and any other applicable organization to determine and electronically present their “ideal” consumer profile and have their advertisement/promotion placed in front of all consumers who match the profile based on the anonymous mining of the consumers actual spending across a broad base of spending categories.

Systems and methods of facilitating transactions related to targeted or customized commercial offerings based on derived sentiment states are provided. The sentiment states are derived from digital representations such as images, videos and sound recordings.

Systems and methods are described for identifying a subset of interest from a general population and for monitoring a database of daily activity logs associated with the general population in order to identify database entries indicative of an occurrence of a pre-defined trigger event that is associated with a member of the subset of interest. In particular, systems and methods are described that allow a massive database of daily activity logs to be monitored to identify trigger events that have occurred within the past twenty-four hours or other very recent time period. Embodiments are described that may be advantageously used by a provider of credit-related products and/or services who wishes to accurately target prospective customers, identified by the system, based on occurrence of a trigger event, as being in a decision-making phase of credit shopping, for purposes of making a timely and targeted offering relevant to the customers' current activities.

A system and method is presented for product substantiation and promotion redemption. A purchased product list is transmitted from a retail store system to a promotion analysis server along with a user identifier. The promotion analysis server identifies promotions available to the user, and then considers whether the benefits under the promotions are still available to the user. Discounts for available promotions related to the purchased product list are calculated and transmitted to the retail store system for deduction from the transactions. An approved product list can be provided that filters the purchased product list before transmittal. The approved product list can include promotions from a plurality of programs.

An apparatus and a method by which a content such as an advertisement corresponding to a user at the reception apparatus side can be selectively outputted to the reception apparatus are provided. A transmission apparatus transmits signaling data (MPD) having a user information setting region, a control information file capable of being accessed or generated applying user information-set data generated by a process for the MPD, and a user information-corresponding advertisement capable of being acquired and reproduced on the basis of description data of the control information file. The reception apparatus sets user information to the user information setting region of the MPD, applies the generated user information-set data to acquire a control information file of a user information-corresponding advertisement, applies the description data of the acquired control information file to acquire the user information-corresponding advertisement, and outputs the user information-corresponding advertisement.

In accordance with some embodiments, a system facilitates the generation of a customized fundraising campaign for an organization by providing mechanisms via which an organizer can set terms of the fundraising campaign and allow participants of the campaign to create customized avatars for use in promoting the campaign. The system generates customized online portals via which participants can make donations or purchase goods to support the organization.

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium. A method includes: for each of a plurality of content items in an inventory of content items: identifying an entity associated with the content item and a plurality of page types for a vertical associated with a product or service described in the content item; locating a plurality of informational pages associated with the entity; classifying each informational page based on the page types; identifying queries associated with the entity, wherein a query is used as a selection criteria for delivering one or more content items associated with the entity; for each informational page of the plurality of informational pages determining relevant queries from the identified queries; and storing in a data structure an association between the content item, data associated with the relevant queries and associated informational pages.

For providing a targeted advertisement to a user, a referral server sends, to a financial platform server, a request for fetching the financial information of the user. The referral server receives, from the financial platform server, a reply containing the financial information of the user. The referral server analyses the financial information of the user to determine one or more behavioural attributes of the user. The referral server uses the one or more behavioural attributes of the user to define a behavioural profile of the user. The referral server may send to a device of the user a code sequence related to a marketing campaign selected according to the behavioural profile of the user. The marketing campaign may be selected by calculating a conversion rate for each of a plurality of marketing campaigns.

This disclosure describes one or more implementations of a model segmentation system that generates accurate audience segments for client devices/individuals utilizing multi-class decision tree machine-learning models. For example, in various implementations, the model segmentation system generates a customized loss penalty matrix from multiple loss penalty matrices. In particular, the model segmentation system can generate regression mappings of model evaluation metrics for a plurality of decision tree models and combine loss penalty matrices based on the regression mappings to generate a customized loss penalty matrix that best fits an administrator's customized needs of segment accuracy and reach. The model segmentation system then utilizes the customized loss penalty matrix to train a multi-class decision tree machine-learning model to classify client devices into non-overlapping audience segments. Further, in one or more implementations, the model segmentation system refines the multi-class decision tree machine-learning model based on adjusting the tree depth.

In various embodiments, promotions are featured on mobile gaming devices. Data based on which a first promotion associated with a first advertiser may be displayed on a mobile gaming device. The data may include a first set of criteria identifying when the first promotion should be displayed.