A digital advertising system includes at least one processor configured to execute a plurality of functional modules including an analytics module to receive and analyze client attributes associated with a website visitor and a requested website to define an analytics event. The analytics module ingests and enriches data within the analytics event and provides it to a machine learning module that generates prediction models for potential bids. A management platform receives the bidding prediction and generates candidate configs. An optimization module receives the candidate configs and applies weights and additional features to select a config and generate an optimized script for the selected config. A deployment module receives the optimized script and delivers the script to the website visitor.

In some embodiments, a method receives an supplemental content placement and a context associated with a request for supplemental content to be displayed for the supplemental content placement. A first value is generated based on the context using a prediction network for a platform. The method determines probabilities for a plurality of types of request actions based on the context. Then, a threshold for the supplemental content placement is calculated based on the first value and the probabilities for the plurality of types of request actions. The method submits the threshold to a platform in a request for the platform to submit a second value for the supplemental content placement.

An analysis system may receive a request to determine a cause of underdelivery for an ad (“query content item”). Properties of the query content item can be processed through a matching model to determine properties of a bid request, thereby generating a bid request. The generated bid request also includes a request for the content server to return a report in response to the bid request regarding ad selection decisions. The bid request may be submitted to the content server, which causes the content server to define a set of candidate content items and select at least one of the candidate content items to submit bids on behalf of in response to the bid request. The content server also provides a report in regarding ad selection decisions. Thus, if the query content item is one of the ads that were not selected, the report may include factors contributing to the query content item not being selected.

Aspects of the subject disclosure may include, for example, embodiments for detecting a navigation application operating on a first communication device, and identifying a location of the first communication device. Further embodiments can include obtaining a first advertisement and a second advertisement according to the location of the first communication device as well as determining a first priority associated with the first advertisement and a second priority associated with the second advertisement. Additional embodiments can include determining the first priority is higher than the second priority resulting in a determination to present the first advertisement prior to the second advertisement, and providing the first advertisement, the second advertisement, and the determination to the first communication device. The first communication device presents the first advertisement within navigation content utilizing the navigation application prior to presenting the second advertisement within the navigation content based on the determination. Other embodiments are disclosed.

Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products for adaptively generating an initial electronic bid value for a new digital content object.

Price mining and dynamic online marketing campaign adjustment data processing systems and methods are disclosed. A system and method for dynamically adjusting an online marketing campaign, in various embodiments, is configured to increase and/or decrease one or more keyword bids that make up part of an online marketing campaign for a particular product from a particular retailer based on whether: (1) the particular product is or is not competitively priced relative to one or more competing retailers; and/or (2) an advertisement for the particular product from the particular retailer on a search engine results page or in an online marketplace is in a relatively desirable position.

Apparatus' and methods are disclosed for distributing sellers' offerings within an advertising system in which a seller generates a profile containing a list of offerings for mobile buyers and wherein mobile buyer's devices display the seller's offerings based on the buyer's preferred purchases or vendors. At least some of the buyer's preferred profile entries are associated with a geographic area. A mobile network is used to connect the mobile buyers and the sellers. The network further includes a brand sponsor that offers branded content through the network and the seller's offering processes. Branded content may be displayed based on a bidding process. Buyers mobile devices may include a bypass function to allow the display of the branded content on the buyer's mobile device even of that branded content does not meet the criteria of the buyer' preferred offerings.

Methods, apparatuses, and systems for facilitating and/or automating project specification, vendor/supplier selection, packaging/processing, and/or mailing for bulk or direct mail campaigns are described herein. Via computer-facilitated techniques, a project manager (or other authorized user) of a mail campaign electronically provides various project information (e.g., project type, design specifications and quantities of materials, mailing list(s), deadlines). Multiple authorized suppliers of services germane to direct mail campaigns (e.g., print shops, lettershops) electronically access the project information and in turn provide respective bids to perform at least some services required by the project. The methods, apparatuses, and systems may also generate logistical recommendations to the user for the bulk or direct mail campaign based on the processed data and on logistical information obtained from a variety of sources.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automated management of campaigns using scripted rules.

Systems and methods for determining location-based bid modifier suggestions include determining a content placement cost based in part on a likelihood of a user that has entered a physical establishment completing a transaction, an average transaction amount for the establishment, and an expected return on investment (ROI). A location-based bid modifier may be determined using the computed cost and a base bid amount. In some implementations, the location-based bid modifier may also be based on a probability model that models the probability of the user visiting the establishment.