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 some implementations, a system may receive an indication that a user device is near a proximate vehicle. The system may obtain a user profile associated with the user device that indicates a vehicle attribute category as being of interest to a user. The system may obtain first audio content based on the proximate vehicle and the vehicle attribute category that describes a proximate vehicle attribute corresponding to the vehicle attribute category. The system may identify, based on the vehicle attribute category, a target vehicle located near the proximate vehicle that compares more favorably to a user preference compared to the proximate vehicle. The system may obtain second audio content based on the target vehicle and the user preference that describes a comparison between the proximate vehicle attribute and a target vehicle attribute of the target vehicle. The system may output the first audio content and the second audio content.

Aspects of the subject disclosure may include, for example, presenting a first model representative of a communication system, receiving, based on the presenting of the first model, a first input that identifies a first communication device included in the communication system, responsive to the receiving of the first input, presenting values for a plurality of operating parameters associated with the first communication device, receiving a second input that includes a modification of at least one value of a parameter included in the plurality of operating parameters, identifying, based on the receiving of the second input, a second model that is dependent on the first model, and modifying the second model based on the identifying of the second model. Other embodiments are disclosed.

Systems and methods for establishing data linkages are described in various embodiments. A system architecture is described which provides a data processing orchestrator device or service which securely interoperates with data sets at various points in time associated with a set of interactions a user may have with computer systems. The data sets are obtained from different data repositories, and are combined together for analysis such that a first data set representing intents (e.g., web search/browse history) can be combined together with a second data set representing outcomes (e.g., purchase transaction history, web site shopping carts).

A system and method for mediated online-advertising providing financially-incentivized, anonymous user-viewing of personalized advertising content through an automated databroker system configured to construct user groups and user group bundles from user profiles and match the user groups and user group bundles with personalized advertiser content received from advertisers in accordance with market stabilizing criteria.

Among other things, advertisements are received for brands or products of brands. Criteria for placement of the advertisements are received at online retail sites. The online retail sites are controlled independently from one another. Inventory data for the products at the online retail sites is received and stored. Data about propensities of the consumers to favor one or more of the brands or one or more products of the brands, from activities of consumers on the online retail sites, is stored. Activity data about current activities of the consumers on the online retail sites is received. One or more of the advertisements are placed on pages served to the online retail sites based on the placement data, the inventory data, the propensity data, and the activity data. Conversion data is received indicating that consumers engaged in conversion events with respect to products associated with the brands or products of brands being advertised. The brands are charged based on the placing of the advertisements and the conversion events. The online retail sites are paid for the placing of the advertisements and the conversion events.

An embodiment of the present disclosure is a system and method for associating advertisers with content creators. The system and method may include determining an association between an advertiser preference profile associated with an advertiser and a user preference profile associated with a content creator to facilitate matching the advertiser with the content creator for an advertiser campaign.

Content relevant to an operator of a music player may be identified using contextual information from music and music player environmental factors. Identification information for a song and music player identification information, environmental information, and listener information may be received. A song may be matched with information in a song categorization database so that one or more categories associated with the song are identified. A listener profile may be matched using a listener knowledge database to identify one or more categories associated with the listener. Content may be selected by matching the one or more song categories with categories in a campaign database and by matching the one or more listener categories with categories in the campaign database. Content includes, but is not limited to, advertising, trivia, referential information, weather, stock market prices, traffic information, news information, social media information, etc. The selected content is sent to the music player.

Systems and methods describe providing a dynamic classification of a vehicle based on motion data captured from sensors. In one embodiment, the system receives motion data for a vehicle, the motion data being captured from one or more sensors; processes the motion data for adjustments; determines maximum acceleration data for the vehicle; calculates a performance metric for the vehicle based on the maximum acceleration data; assigns one or more designations to the vehicle based on the performance metric; and presents the one or more designations of the vehicle to one or more users of a network-connected platform. In some embodiments, designations may relate to, for example, racing classes for vehicles entering into racing competitions, or handicap designations to level the playing field among different racing competitors.