A change in a weighting coefficient for an explanatory variable in an objective function used to optimize a target is received, and the target is optimized based on the objective function to which the changed weighting coefficient has been applied.

The present disclosure provides a computer-implemented method and system for running high performance marketing campaigns for granular-level segments of users in real-time. The computer-implemented method and system corresponds to a user segmentation system. The user segmentation system receives a first set of data associated with a plurality of users. The user segmentation system fetches a second set of data. The user segmentation system obtains a third set of data. The user segmentation system analyzes the first set of data, the second set of data and the third set of data. The user segmentation system enables segmentation of the plurality of users. The user segmentation system assigns one or more segment goals. The user segmentation system creates a plurality of micro-segments. The user segmentation system triggers initialization of one or more marketing campaigns. The user segmentation system predicts performance of each of the one or more marketing campaigns.

Embodiments of the present disclosure provide improved methods, systems, devices, media, techniques, and processes, often computer-based and/or processor-based, for advertising to consumers, such as consumers of music-based products. In a first part of the disclosed methods and systems, potential sales of a product can be predicted. In a second part of the disclosed methods and systems, one or more regression strategies can be used to analyze data from previous products in order to produce optimized parameter values. In a third part of the disclosed methods and systems, advertisement performance can be monitored and input parameters adjusted based on that performance.

In many embodiments, a system comprising one or more processor and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: determining a set of questions associated with a campaign by extracting text from one or more advertisements; generating vector embeddings of one or more online activities of a user; receiving a search query from a graphical user interface of a computing device of the user; determining a second question from the set of questions to present to the user based on respective relevance probabilities; determining a confidence score associated with the second question; and when the confidence score associated with the second question exceeds a second predetermined threshold, presenting the second question to the user via the graphical user interface. Other embodiments of related methods and systems are also provided.

A computer-implemented system including a data store: a content items database, a user account database, and one or more servers configured to execute a computer program to perform one or more of the following: receiving content items from content database that are associated with a topic selected by a user for posting on a social network, wherein at least one content item is associated with an URL; estimating a post to a reaction filter for a time interval for the social network for the user, calculating a reaction profile associated with reactions to posts on the social network by aggregating reaction time of a plurality of users on the social network for one or more content items posted on the social network; determining a schedule for posting the content items on the social network as a function of the post to reaction filter and reaction profile.

A system for managing customer feedback regarding a product or service is disclosed, particularly, at a point-of-sale location. The system includes a backend system and a frontend system wherein feedback from a customer regarding the product or service is collected using the frontend system. The feedback is transmitted to the backend system where one or more sales or business hypothesis are generated to present to the customer to acquire further feedback from the customer. One or more action items, such as product offering optimization, marketing campaign customization, and inventory management can be suggested based on the customer response to the generated hypothesis.

A method comprises receiving an ad event data including data about a plurality of ad events, and including a user ID and an ad ID for each ad event in the ad event data set, where the ad event data set has been anonymized applying a one-way encryption key for each user ID in the ad event data set, and a two-way encryption key for the ad ID in the ad event data set. The attribution processor receives a customer data set including data about a plurality of customers, including a user ID and a customer value for each customer, where the customer data set has been anonymized using the one-way encryption key for each user ID in the data, and a private encryption key for the customer value. Without decrypting the received ad event data set and the received customer data set, the processor then matches ad events for each conversion by comparing the user IDs in the encrypted ad event data set to the user IDs in the encrypted customer data set to create a set of contributing ad events, assigns a share of the customer value to each relevant ad event, sums homomorphically the encrypted customer values for contributing events, and determines a recommendation for serving advertisements.

A system collects information from different sources regarding online activities of users and information regarding presentation of additional content. The user online activity information can include an indication of a web page visited (e.g., URL), a time when the web page was visited, and an anonymized identifier for a user device. Additional content service information can include an additional content identifier, a time the additional content was served, and an anonymized identifier for a user device to which the additional content was served. An optimizing engine uses this information to correlate additional content presentation to user online activity while preserving privacy of users. The system can use the correlation information to perform various statistical analyses, including determining the effects of presentation of particular additional content on user online activity, while preserving the privacy of individual users and preventing the information from being linked to a particular user.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, to improve the impact of digital media. One of these methods includes providing a non-affiliated advertisement to a plurality of users. The method includes receiving indications that a subset of the plurality of users have viewed the non-affiliated advertisement. The method also includes creating a control group for an advertisement from the subset of the plurality of users that received the non-affiliated advertisement.

Provided herein are systems, methods and computer readable media for programmatically generating and/or revising promotions for a provider as well as generating and providing analytics data regarding currently offered promotions in real-time. In providing such functionality, the system can be configured to, for example, monitor and analyze various promotions, including current promotions and analytics data about promotion-related purchases, that enable the system to determine the relative successfulness of a promotion for a provider and/or category of provider. Upon determining what has been more successful or is expected to be a more successful promotion for a provider, the system can present the promotion to the provider for approval and/or make the promotion to consumers programmatically. In some embodiments, the system may be further configured to revise the promotion programmatically and/or upon receiving the provider's approval of the programmatically generated proposed edits to the promotion parameters.