A method of delivering advertising in an online environment includes determining a context of a user operating a client computer to interact with an e-commerce website, where the determined context representing an intent of the user to locate a product for purchase, defining a relation between one or more of a plurality of advertisements and the product based on at least one of a plurality of relevance types, and displaying, to the user, at least one of the advertisements having the relation to the product.

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.

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.

The present invention is directed to machine-learning based methods and systems related to dynamically inserting items multimedia content into media broadcasts. By using machine-learning based models, the performance of different items of multimedia content with different audiences can be automatically simulated, resulting in recommendations for where, when and how to optimally distribute those items of multimedia content. The multimedia content can be distributed by dynamically integrating that multimedia content into a streaming video feed. The reaction of an audience to the multimedia content is then automatically monitored, collected, and analyzed using machine-learning techniques, allowing the reaction of the audience to the multimedia content to be automatically determined. This reaction can then be input back into the machine-learning based simulator, further refining future predictions for the performance of items of multimedia content with audiences.

Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products that provide for an improved and more efficient system for transmitting content to client devices. The embodiments disclose an apparatus that clusters user behavior based on platform session records. The platform session records comprise stored data associated with a plurality of user inputs received by the system for the duration of a platform session. The apparatus and methods transform the platform session records into data comprising a form that is usable for identifying clusters of platform sessions. As a result of the clustering methodologies, the apparatus is configured to deliver content specifically optimized for users of client devices. The present disclosure thus provides for an improved networked system that reduces the amount of data transferred via the network and allows for a more efficient system that has reduced infrastructure requirements and improved performance.

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

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.

Systems, methods, and non-transitory computer readable media can determine a representation of an advertisement based on a first machine learning model. The representation can be provided to a second machine learning model. One or more qualitative ratings associated with the advertisement can be determined based on the second machine learning model.

The presented technology is directed to devices, systems, and their methods of use for evaluating and optimizing the effectiveness of digital advertisements to increase sales such as in a digital ad-buying platform. In particular, the presented platform is configured for determining incremental lift of a product due to an advertisement and/or a promotion that is distributed online. Presented herein, therefore, are devices, systems, and methods of monitoring, measuring, and/or optimizing lift of an advertising campaign, such as a real-time, digital ad buying campaign implemented by a suitably configured advertising platform.

A method, system and/or computer usable program product for automatically managing the conveying of messages among multiple communication channels including (i) receiving, from a first computing system, an on-line message addressed to a user, (ii) automatically categorizing the message among a predetermined set of message categories stored in memory, (iii) identifying a set of on-line message channels preselected by the addressee user for receiving messages for each of the predetermined set of message categories, (iv) identifying a set of performance metrics stored in memory for optimizing message channel selection, (v) utilizing the performance metrics to automatically select an optimum message channel from the preselected message channels for sending the categorized message to a second computing system of the addressee user, (vi) automatically formatting the categorized message for the optimum message channel, and (vii) sending the formatted message on-line to the second computing system of the addressee user across the optimum message channel.