Abstract: Systems, methods and media for adaptive real time modeling and scoring are provided. In one example, a system for automatically generating predictive scoring models comprises a trigger component to determine, based on a threshold or trigger, such as a detection of new significant relationships, whether a predictive scoring model is ready for a refresh or regeneration. An automated modeling sufficiency checker receives and transforms user-selectable system input data. The user-selectable system input data may comprise at least one of email, display or social media traffic. An adaptive modeling engine operably connected to the trigger component and modeling sufficiency checker is configured to monitor and identify a change in the input data and, based on an identified change in the input data, automatically refresh or regenerate the scoring model for calculating new lead scores. A refreshed or regenerated predictive scoring model is output.

Abstract: A system for training a bidding model comprising: a plurality of tactics stored on at least one database; a plurality of hyperparameters; in response to an available inventory from a publisher relayed through a real time bid server, computing a bid on the available inventory; sending the bid to the real time bid server; receiving an auction result in response to the bid; calculating a plurality of rewards based on the auction result and the tactics; calculate a plurality of q values based on the rewards; calculate a plurality of losses; backpropogating the losses through the bidding model.

Abstract: Dynamic content can be delivered via email. Email messages include HTML content with one or more hyperlinks referring to a network-connected dynamic content server. The hyperlinks are accessed upon rendering of the email on a client device, triggering a request to a dynamic content server. The dynamic content server determines a content item to be served in response to the request. The dynamic content item determination may be based on factors including the identity of the requester, the email communication in which the hyperlink is embedded, recent activities or behavior on the part of the requester, and/or known preference or demographic information associated with the requester. The request can be directed to a selected content item stored within a content delivery network, for transmission back to the requester and display to the user within the email.

Abstract: The subject technology provides a targeted content curation and placement optimization system comprising a processor connected to a publication network, the publication network navigated by an online consumer seeking actionable content. An online demand side portal is accessible, via the publication network, to a content provider. An online supply side portal is accessible, via the network, to a publisher of content on the publication network. An integrated bidding exchange is communicatively coupled to the demand side portal and the supply side portal and presents user interfaces enabling receipt of bids from the content provider for placement of content by the publisher at a specified location or domain on the publication network. A geographic insights generator may generate geo-specific intender attributes that may be used to curate the targeted content and optimize one or more bidding parameters of the content provider.

Abstract: Methods and systems for performing targeted advertising are described. Relative concentration of consumer types in the audience of particular media content is determined by measuring the coincidence of key values identifying certain consumer types, and other key values identifying audiences of particular media content, in a database.

Abstract: A computer implemented method, comprising: selecting a plurality of dynamic models for evaluating a scoring request, wherein the dynamic models are stored on a scoring database; deploying each of the dynamic models to one of a plurality of evaluators; synchronizing the dynamic models, the synchronizing including at least determining a same version of the dynamic models is deployed and available to all evaluators; receiving, at a scoring node, a scoring request for a score of a lead from at least one requester; separating the scoring request into a plurality of scoring requests, wherein each of the scoring requests is assigned to one of the selected dynamic models wherein the request is separated by model and aggregate model results and sent to an evaluator queue; combining results from each of the dynamic models; evaluating the combined results wherein each of the evaluators sends a model evaluation response to the response queue; and providing a response to the scoring request based on the evaluation of the

Abstract: Dynamic content can be delivered via email. Email messages include HTML content with one or more hyperlinks referring to a network-connected dynamic content server. The hyperlinks are accessed upon rendering of the email on a client device, triggering a request to a dynamic content server. The dynamic content server determines a content item to be served in response to the request. The dynamic content item determination may be based on factors including the identity of the requester, the email communication in which the hyperlink is embedded, recent activities or behavior on the part of the requester, and/or known preference or demographic information associated with the requester. The request can be directed to a selected content item stored within a content delivery network, for transmission back to the requester and display to the user within the email.

Abstract: In one embodiment, a method includes accessing a current-visitor context of a current visitor to a web page in a current web-browsing session. The current-visitor context includes one or more data associated with or concerning the current visitor. The method includes selecting based on the current-visitor context a particular one of multiple possible instances of the web page for presentation to the current visitor. The particular one of the multiple possible instances of the web page is substantially most likely to generate a highest expected outcome from interaction with the web page by the current visitor as indicated by the current-visitor context.

Abstract: An ad collision machine can be configured to evaluate collision queries for possible ad collisions and is associated with an ad datacenter configured to evaluate and respond to bid requests on behalf of a plurality of advertisers. The ad collision machine can comprise a plurality of nodes and a data cache containing a plurality of user ID—campaign ID keys representing recently submitted bids in response to bid requests. Once a selected node receives a collision query, a user ID—campaign ID key is retrieved from the collision query. If the first key is not found in the data cache, it is written to the data cache by the node and the ad collision machine returns that user ID—campaign ID pair as available to be bid on.

Abstract: In some examples, a computer-implemented method of managing an advertising exchange is provided. The method uses email data and provides an interactive user interface for controlling management of data in an email channel. One or more inputs of online audience data is received. The online audience data includes email channel inventory from multiple publishers, Offline audience data including offline shopping behavior is sourced from at least one or more offline source. The online audience data and the offline audience data is included in a unified customer database, and the interactive user interface includes interface elements selectable to present online and offline audience data sourced from the unified customer database.

Abstract: In some examples, a system comprises at least one programmable processor; and a machine-readable medium having instructions stored thereon which, when executed by the at least one programmable processor, cause the at least one programmable processor to execute operations comprising: receiving a first request from at least one user device to execute an instance of an application; transmitting a graphical user interface (GUI) to the at least one user device to be rendered on a display of the at least one user device; receiving a second request, via the GUI, from the at least one user device, to deploy a digital advertisement, the second request including a set of platforms of a plurality of platforms of a multi-platform integration system, a set of settings, a set of parameters, and a set of allocation data; interfacing with each one of the platforms in the set of platforms; and integrating a digital advertisement directly with each one of the platforms in the set of platforms based on the set of settings, the

Abstract: Processes and apparatuses for content personalization are provided, providing for rule configuration. Content personalization systems interpret user behavior and attributes along with the content users are interacting with, to build optimized predictive models of what content the user may want to see next. Those predictive models can be utilized to personalize content in one or more environments, including email, mobile and applications. Rules include filters applied to the predictive model output and/or the overall system output. Filters can be prioritized and iteratively applied or removed to adjust system output to satisfy desired result set criteria.

Abstract: The subject technology identifies a series of journey event types in an online user journey, the event types including an impression event, an email event, a click event, and a website visit, and assigns an encoder to each event type. Using an assigned encoder, the technology encodes each event type to generate an encoded vector for each event type. The encoded vector is representative of at least a portion of the online user journey relating to that event type. The technology generates an encoded vector for each event type to create a set of encoded vectors, the set of encoded vectors including one or more of an impression event encoded vector, an email event encoded vector, a click event encoded vector, and a website visit encoded vector.

Abstract: A computer-implemented method for generating content recommendations for content items, each content item associated with one of a plurality of customers, the method comprising: receiving, by a network-connected server, a content request from a requesting user, the content request comprising a user identifier and a customer identifier; retrieving request parameters from a computer-implemented parameter service, the request parameters comprising indicia of a plurality of models and parameters for the models; retrieving user data comprising a set of indicia of recommendable resources associated with the customer identifier; routing the content request, request parameters and user data to a plurality of ranking and optimization component, each component generating a recommendation score for each recommendable resource; generating content recommendations based on the recommendation score which content recommendations are returned to the requesting user and stored by the server as a recommendation event within a r

Abstract: A system comprising a computer-readable storage medium storing at least one program, and a computer-implemented method for referring contacts to receive text message alerts. An accounts module receives first user data including an indicator that a first user requested to subscribe to receive text messages alerts. The account module adds, based at least on the received first user data, a first user account to a database of subscribers. A message generator module generates, using the processor in response to receiving the first user data, a first text message corresponding to an offer to subscribe to receive text message alerts. A communication module transmits to the first user the first text message corresponding to the offer to subscribe to receive text message alerts. The transmitted first text message can be forwarded to a second user.

Abstract: A data enrichment system for enriching requests for advertising opportunities. The data enrichment system is configured to aggregate and index data to provide end user insights to marketers based upon information supplied by publishers in regards to advertising opportunities passed along in requests. The system is configured to take attributes passed along in a request associated with the advertising opportunity and provide enriched data based upon the attributes received in the request. The attributes can then identify corresponding enriched data that can be passed along to the marketers.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method that enables short message service (SMS) text messaging to be integrated into existing applications is presented. Consistent with some embodiments, the method may include receiving a request from a client application to transmit a message to a recipient device. The method may further include adding the message transmission request to an outbound queue based on determining the message transmission request is valid. In response to successfully validating the request, the method causes transmission of the message to the recipient device.

Abstract: In some examples, a system for determining a level of self-image congruence comprises at least one processor and a memory storing instructions which, when executed by the at least one processor among the processors, cause the system to perform operations comprising, at least: selecting one or more self-image attributes that align with a brand-user image; defining each of the selected self-image attributes via a type of subject matter that is of interest to consumers identifying with the selected attributes; identify consumers exhibiting one or more of the selected attributes based on a digital footprint including an online content consumption; computing a congruence score for each identified consumer relative to each selected attribute; and rating the resulting set of consumers based on their respective congruence scores for the selected attributes.

Abstract: A system for training a bidding model comprising: a plurality of tactics stored on at least one database; a plurality of hyperparameters; in response to an available inventory from a publisher relayed through a real time bid server, computing a bid on the available inventory; sending the bid to the real time bid server; receiving an auction result in response to the bid; calculating a plurality of rewards based on the auction result and the tactics; calculate a plurality of q values based on the rewards; calculate a plurality of losses; backpropogating the losses through the bidding model.

Abstract: In accordance with embodiments of the present disclosure, each third party system of multiple third party systems can store files including datasets associated with one or more campaigns. A computing system can be in communication with the third party systems and including a first database and a second database. The computing system can be configured to receive the selection of the one or more third-party systems, store metadata associated with the at least one campaign in the first database, calculate at least one discrepant data value between the one or more third party systems, based on the datasets associated with the at least one campaign from each of the one or more third party systems.