Abstract:
Systems, devices, and methods are disclosed for determining the quality of traffic received from different web page publishers, and setting a pricing structure for the different traffic based on the determined quality of traffic. Accurately determining the quality of traffic and/or clicks from different publishers allows the network system described herein to offer a fair marketplace with just return on investments (ROI) for advertisers, and offer a robust and accurate traffic quality based pricing model for publishers. Internet based technology, and in particular deep learning techniques available through a neural network, are utilized to determine the pricing structure based on click and/or web page traffic quality measurements generated through the deep learning techniques.
Abstract:
Systems and methods for are provided for measuring treatment effect of advertisement campaigns. The system includes a processor and a non-transitory storage medium accessible to the processor. The system includes a memory storing a database including historical advertisement data. A computer server is in communication with the memory and the database, the computer server programmed to obtain a tree-based model using the historical advertisement data, where the tree-based model include a plurality of leaf nodes. Within at least one leaf node of the tree-based model, the computer server obtains a number of subjects and estimates a treatment effect for a treatment. The computer server calculates a final treatment effect for the tree-based model using the number of subjects and the treatment effect. The computer server then determines a parameter for future advertising strategy using the final treatment effect.
Abstract:
Systems and methods for managing advertisement campaign are provided. The system includes one or more devices having a processor and a non-transitory storage medium accessible to the hardware processor. The system includes a memory storing a database including campaign data. The system also includes a server computer in communication with the database. The server computer is programmed to receive a budget to be spent on a plurality of websites. The server computer is programmed to estimate a parameter for a non-linear model based on the campaign data. The server computer is programmed to estimate an expected number of conversions for each of the plurality of websites using the non-linear model with the estimated parameter. The server computer is programmed to determine an allocation of impressions for the plurality of websites that maximizes an estimated total number of conversions.
Abstract:
Systems and methods for tracking brand reputation and market share are provided. The system includes one or more devices having a processor and a non-transitory storage medium accessible to the hardware processor. The device is programmed to obtain an awareness index at a plurality of levels at least partially based on the brand data. The device is programmed to obtain a favorability index as a ratio of user numbers based on the brand data. The device is programmed to obtain a branding index by combining the awareness index and the favorability index. The device is programmed to obtain an affinity score for a group of users at least partially based on the brand data and recommend the group of users based on the affinity score to increase the branding index.