A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: tracking touchpoints by a user over a first time period; after receiving an order, determining, using a machine-learning model, a respective contribution of each of the touchpoints, wherein the machine-learning model is trained to predict a probability of the user placing the order during a second time period based on an input feature vector representing a set of touchpoints; and allocating a respective percentage of credit for the order to the each of the touchpoints based on the respective contributions of the each of the touchpoints. Other embodiments are disclosed.

The computing device receives data for a plurality of events that includes a timestamp associated with a digital traffic campaign in an event processing system. Based on the timestamp of the data for each event, the computing device executes operations comprising: applying filtering using digital signal processing to the event count for the combined data for each of the one or more intervals, executing a model to compute one or more backward difference approximations for the one or more candidate systems time constants from the evaluated exponential curve, and selecting a system time constant that predicts a first time instant wherein the data for the plurality of events approaches a point on a horizontal asymptote for the evaluated exponential curve. The computing device determines an epoch for the selected system time constant and outputs the determined epoch for the selected system time constant in the graphical user interface.

The present disclosure provides techniques for presenting a reward impression. A computing system can receive, from a client device, a request to view the reward impression having a first time slot and a second time slot. The computing system can calculate a first conversion rate associated with a first content item being presented in the first time slot and a second conversion rate associated with a second content item being presented in the second time slot. The computing system can select, using the one or more machine-learned models based on the first conversion rate and the second conversion rate, the first content item and the second content item from a plurality of content items. The computing system can cause the presentation of the first content item in the first time slot and the second content item in the second time slot of the reward impression.

Systems and methods for estimating advertisement impressions needed for detecting sales lift are disclosed. In some embodiments, based on an impression estimation request received from a computing device, a disclosed system determines an item set including items proposed to be advertised with an advertising campaign, and a time period proposed for the advertising campaign. Based on at least one model and historical transaction data associated with the item set, control sales data in the time period is computed for the item set without the advertising campaign. Based on a trained model and additional data associated with the item set, the system computes a number of impressions needed to detect a target sales lift compared to the control sales data in the time period for the item set with the advertising campaign. Based on the number of impressions, the system generates and transmits estimated impression data to the computing device.

A system for processing images captured in a retail store is provided. The system may include a processor configured to: access a database storing a group of product models; receive an image depicting at least part of a store shelf having a plurality of products of a same type displayed thereon; analyze the image and determine a first candidate type of the products based on the group of product models and the image analysis; determine a first confidence level associated with the first candidate type; when the first confidence level is below a confidence threshold, determine a second candidate type of the products using contextual information; determine a second confidence level associated with the determined second candidate type of the plurality of products; and when the second confidence level is above the confidence threshold, initiate an action to update the group of product models stored in the database.

The invention relates to a system used to enhance the results of a direct mail marketing campaign. The system processes spanning online and offline efforts with the end result being increased engagement and return on investment through added impressions and real-time Key Performance Indicator (KPI) reporting, in an easy to use and understand dashboard. Additionally, the system has a smart label which communicates with the system of the instant invention to track mail.

A computer-implemented method and system for advertising that performs the steps of delivering an electronic advertisement comprising one or more menu options and a reference to a network location for retrieving specified content associated with each menu option for inclusion in a first electronic document, receiving a selection of one or more menu options from the electronic advertisement and delivering a subsequent accessible document including content from the referenced network location associated with the menu option selected, the subsequent accessible document including the electronic advertisement.

Systems and methods are disclosed for conducting media lift studies for online advertising concurrently with operating an advertising campaign. While operating an advertising campaign for a first advertiser/client focused primarily on a set of intended ads and a specific targeted viewer audience, a non-intended ad is occasionally substituted to run in an ad slot, and is tracked as belonging to the first advertiser/client. The non-intended ad can be for example one of: an ad for a second advertiser/client; an alternate ad for the first advertiser/client; or a blank/unrelated ad. After the campaign, attribution results for the intended ads are adjusted according to those for non-intended ads to provide an indication of net media lift resulting from the intended adstypically at no additional cost to the first advertiser/client. Analysis results may also be compared between different attribution data providers to determine which provide the more accurate attribution data.

A system and method enable exploration of cold ads in an online information system. Cold ads are ads that are new to the system and do not yet have reliable click through rate (CTR) estimates or click probabilities. The method and system selectively boost the click probabilities of cold ads to increase their likelihood of participating in and winning an auction so that the cold ad get more impressions, but without adversely affecting revenue in a production environment when cold ads are introduced.

A cross-platform management system that handles cross-platform management of client requirements receives a request corresponding to a plurality of client-defined requirements to be achieved in a flight. The request for the plurality of client-defined requirements is associated with one or more request parameters. The system generates a proposal plan corresponding to the received request based on adjustment of the one or more request parameters. The proposal plan corresponds to at least a distribution of target audience across a set of delivery platforms. The system executes the generated proposal plan for a first time period in the flight on one or more delivery platforms. The system re-optimizes the generated proposal plan and controls execution of the generated proposal plan for a second time period in the flight by an in-flight re-distribution of the target audience across one or more delivery platforms of the set of delivery platforms.