Embodiments of system are disclosed in which selection strategies for a direct marketing campaign that identify consumers from a credit bureau or other consumer database can be planned, tested, and/or refined on a stable subset of the credit database. In some embodiments, once refined, consumer selection criteria may be used to execute the direct marketing campaign on the full consumer/credit database, which is preferably updated approximately twice weekly. In one preferred embodiment, the data for the test database represents a random sampling of approximately 10% of the full database and the sampling is regenerated approximately weekly in order to provide a stable set of data on which campaign developers may test their campaign. For each consumer in the sampling, the environment may allow a client to access and use both attributes calculated by the credit bureau and proprietary attributes and data owned by the client. The system allows for a plurality of clients to use the system substantially simultaneously while protecting the privacy and integrity of the client's proprietary data and results.

An online system estimates a lift in foot traffic at a store in response to an advertisement campaign at the online system. The online system identifies a physical location for the store and obtains location data for a base group of users and a lifted group of users, where the lifted group of users receives advertisements associated with the store and the base group of users does not. The online system computes a distance between the location of the store and the user's location to create a base distance array for the base group and a lifted distance array for the lifted group. The online system then determines an aggregate value that represents a measure of a number of users visiting the store for each of the base distance array and the lifted distance array, and estimates a lift in foot traffic by comparing the two aggregate values.

A system for providing an online advertising platform includes a first non-transitory machine-readable medium storing instructions executable by one or more data processors to group impression inventory units based at least in part on performance characteristics of the impression inventory units.

Methods, systems, and apparatus include computer program encoded on a computer-readable storage medium for conducting an experiment for a campaign. A subset of current campaign parameters from a third party can be received, by a computing system, to be a set of test variables, where the set of test variables correspond to a proposed modification of a current campaign that is applied to a treatment campaign. The current campaign can be monitored for changes to the current campaign parameters. Based on a determination that the current campaign parameter that has been modified by the third party is outside the set of test variables, the modification to the current campaign parameter can be reproduced and propagated to the treatment campaign. An action to take can be determined based on the modified current campaign parameter causing a change to at least one of the set of test variables.

A computer-implemented method for dynamic link redirection includes receiving a request to display online content to a user, determining a plurality of current content links in the online content, for each current content link among the plurality of current content links, performing operations including: obtaining current assessment parameters for the current content link, generating a current assessment for the current content link based on the current assessment parameters, obtaining a plurality of alternative content links based on the current content link, generating a plurality of alternative assessments for each alternative content link among the plurality of alternative content links based on respective alternative assessment parameters for the alternative content link, determining a selected content link among the plurality of alternative content links based on the current assessment and the plurality of alternative assessments, replacing the current content link in the online content with the selected content link, and displaying the online content to the user.

Systems, apparatuses, and methods obtain and process data that may be used to identify or discover one or more influencers in business, finance, fashion, sports, current events, and other areas, and also to generate an indication of each influencer's expertise and ability to influence others with their posts or comments. A measure of each influencer's accuracy with regards to the contents of their previous comments or posts may also be generated. Based on determining the sentiment associated with each influencer's current posts or comments, an index or measure of the accuracy weighted sentiment expressed by a set of influencers with regards to an event, stock, trend, or other aspect may be generated and presented to a user to assist them in making a decision.

According to the embodiments of the present disclosure, a method, an apparatus, a device, a storage medium and a program product for promoter determination are provided. The method includes: recalling, from a set of promoters, a plurality of candidate promoters for a target provider, the target provider being capable of providing at least one object available to a user, the plurality of candidate promoters being capable of publishing guidance contents for guiding a user to acquire a corresponding object; determining, based on a first feature of the target provider and second features of the plurality of candidate promoters, priority levels of the plurality of candidate promoters; and determining, based on the priority levels, a target promoter for the target provider from the plurality of candidate promoters.

Executing 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: receiving, by a graphical processing unit (GPU) server, a dataset transformed by a storage system that is external to the GPU server; and executing, by the GPU server, one or more machine learning algorithms using the transformed dataset as input.

A digital ad-buying platform uses counterfactual-based incrementality measurement by implementing randomization and/or a correction for auction win bias to avoid the need to identify counterfactual winner types in the control group. This approach can estimate impact at the individual consumer level. Confidence levels can be determined using Gibbs sampling in the context of causal analysis in the presence of non-compliance.

Methods, systems, apparatus, and articles of manufacture to determine causal effects are disclosed herein. An example apparatus includes a weighting engine to calculate a first set of weights corresponding to a first treatment dataset, a second set of weights corresponding to a second treatment dataset, and a third set of weights corresponding to a control dataset, the weighting engine to increase an operational efficiency of the apparatus by calculating the first set of weights, second set of weights, and third set of weights independently, a weighting response engine to calculate a first weighted response for the first treatment dataset, a second weighted response for the second treatment dataset, and determine a causal effect between the first treatment dataset and the second treatment dataset based on a difference between the first weighted response and the second weighted response, and a report generator to transmit a report to an audience measurement entity.