The effectiveness of advertisements with respect to a group of panelists is measured. Based on the results of such analysis, advertisements and/or variants thereof are selected for presentation to consumers. Effectiveness of advertisements is measured, in one embodiment, by detecting exposure to advertisements, and then monitoring panelist behavior following exposure to an advertisement. In one embodiment, the group of panelists is a representative sample of a larger population, so that observations of panelist behavior can be used as a basis for making decisions regarding presentation of advertisements to a larger audience having characteristics similar to those of the panelists.

Once the relative effectiveness for various audiences has been determined, advertisements can be selected for presentation to individual consumers or to groups of consumers, so as to maximize effectiveness. In one embodiment, such analysis and selection is performed substantially in real-time.

One or more computing devices, systems, and/or methods for isolated budget utilization are provided. A first budget pacing component is assigned to control bidding by a first content serving component for a set of content items. A second budget pacing component is assigned to control bidding by a second content serving component for the set of content items. The first budget pacing component controls the bidding by the first content serving component according to a first portion of a content item budget based upon a traffic share of the first content serving component. The second budget pacing component controls the bidding by the second content serving component according to a second portion of the content item budget based upon a traffic share of the second content serving component.

This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Service provider (SP) system within a special purpose hardware platform operable to present an advertisement campaign to a potential customer, including a contact indicium. The SP system may include a contact interface, such as a short message service terminal, telephone interface, or web-based server interface, for establishing contact with the prospective customer. The contact interface may be used to determine, and store contact information associated with the prospective customer, which is associated with the advertisement campaign and provided to the service provider for further processing.

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and cause the one or more processors to perform (1) receiving a request to generate one or more campaigns; (2) determining one or more predicted bids for one or more keywords in the one or more campaigns; (3) adjusting the one or more predicted bids for the one or more campaigns; (4) pacing the one or more predicted bid, as adjusted, for the one or more campaigns; and repeating (2)-(4) at one or more periodic intervals. Other embodiments are disclosed herein.

A system including one or more processors and one or more non-transitory computer readable media storing computing instructions that, when executed on the one or more processors, perform: receiving user session activity information and campaign impression information; determining a sample of the user session activity information and the campaign impression information based on a sampling criterion; analyzing the sample using (i) a first logistic regression model and (ii) a second linear regression model; determining a weighting value for the campaign impression information based on a first output of the first logistic regression model and a second output of the second linear regression model; and determining a sub cut lift measurement for the campaign impression information based on a first lift measurement for the campaign impression information and the weighting value for the campaign impression information. Other embodiments are described.

A computer implemented method of adapting an application according to user interaction comprising using one or more processors for executing a code for collecting autonomously a plurality of action events describing a plurality of actions taken by a plurality of users to navigate through a plurality of pages presented by an application to accomplish one or more goals of the application, the plurality of pages are presented on a GUI at a plurality of user devices used by the plurality of users, analyzing the action events to identify one or more behavioral patterns of at least some of the users for accomplishing the goal(s) and generating automatically one or more recommended adaptations for the application according to the behavioral pattern(s) to adapt a layout of the application in order to increase a probability for one or more users to successfully accomplish the goal(s).

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for managing application program interface calls.

Generating a transformed dataset for use by a machine learning model in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: storing, within one or more storage systems, a transformed dataset generated by applying one or more transformations to a dataset that are identified based on one or more expected input formats of data received as input data by one or more machine learning models to be executed on one or more servers; and transmitting, from the one or more storage systems to the one or more servers without reapplying the one or more transformations on the dataset, the transformed dataset including data in the one or more expected formats of data to be received as input data by the one or more machine learning models.

A method for identifying segments of a population of user devices communicating on a communications network. The segments correspond to user devices of the population exhibiting comparable behavioral patterns detectable by the communications network. A plurality of marketing systems are accessible on the communications network, and each of the plurality of marketing systems include respective use data corresponding to respective ones of the population for the marketing system. The method includes retrieving by a processor the respective use data for the population, from the plurality of marketing systems, determining by the processor if the respective use data exceeds a threshold for particular behavioral pattern of interest, for the respective use data, determining by the processor a unique identifier for each user device of the use data, grouping by the processor in a database, the respective use data in relation to the unique identifier, for each user device of the use data that exceeds the threshold, and mapping by the processor in the database, the behavioral pattern of the respective use data for each user device of the use data that exceeds the threshold. Behavioral patterns are determined for the respective segment, and related to the user devices of the segment. Content for delivery to the segment is sequenced, and placeholder in the sequence is stored in relation to each user device of the segment, to ensure that each next sequential content is delivered to the respective user device.