Embodiments of systems and methods for the aggregation, analysis, display and monetization of pricing data for commodities in general, and which may be particularly useful applied to vehicles are disclosed. Specifically, in certain embodiments, historical transaction data associated with a particular vehicle configuration may be obtained and processed to determine pricing data associated with the vehicle configuration. The historical transaction data or determined pricing data may then be presented in an intuitive manner.

Methods and systems for analyzing and evaluating item recommendations presented on a web site are disclosed. In one aspect, a user interface is generated for display on a website. Item recommendations personalized for an individual user are displayed within in item recommendation region of the website. Impression, clickstream, and sales data are received from user activity on the website. The impression, clickstream, and sales data are displayed on a dashboard of an administrator user interface. An administrator user can select visualizations to display on the dashboard using selectors for impressions, clicks, sales, users, and time. Two or more sets of data can be overlaid to illustrate relationships between user interactions with recommended items and actual sales of those items. The dashboard is dynamically updated in response to new data received from the website in real-time.

A digital advertising system includes at least one processor configured to execute a plurality of functional modules including an analytics module to receive and analyze client attributes associated with a website visitor and a requested website to define an analytics event. The analytics module ingests and enriches data within the analytics event and provides it to a machine learning module that generates prediction models for potential bids. A management platform receives the bidding prediction and generates candidate configs. An optimization module receives the candidate configs and applies weights and additional features to select a config and generate an optimized script for the selected config. A deployment module receives the optimized script and delivers the script to the website visitor.

Embodiments of the present disclosure include apparatuses, computer-implemented methods, and computer program products for automatic product verification and shelf product gap analysis. Some embodiments utilize a multi-imager imaging engine to capture at least two image data objects associated with at least a near field and a far field via corresponding near and far-field imagers. The far field image data object in some embodiments is processed to identify, and/or detect and decode, product information on a product label at a shelving location for future processing. The near-field image data object may be processed to identify a product set located within the environment surrounding the product label. The information identified from each image data object may be processed to identify whether one or more product mismatches, pricing mismatches, and/or product gaps are present at the shelving location, with improved likelihood of success for each task.

A method and system for managing, in real time and over time includes an electronic device with at least a processor, a memory and a display coupled to the processor and at least one network connection and an interactive management tool coupled to the electronic device. The interactive management tool includes features for managing captured leads such as Email Alerts, Exporting, Labels, Syncing, Value, and Mobility. Also provided is a method for utilizing the system to capture leads and to interactively manage the same. Further provided herein is a non-transitory machine-readable storage device comprising processor-executable instructions to perform the method.

A method includes receiving, by a computing device of a media service provider, a search request associated with a first product. The search request is received from a media device associated with a subscriber of a service provided by the media service provider. The method includes, in response to the search request, determining, by the computing device, a responsible party associated with the first product based on a purchase date of the first product and a return period for the first product. The method also includes sending, from the computing device to the media device, contact information of the responsible party. The contact information is to be displayed by the media device to a display device with an option to contact the responsible party.

In an example, a subject using a user mobile-identification-credential device (UMD) requests vetting by a vetting system, which receives verified subject information associated with a level-n mobile identification credential (MIC-n) that UMD received from a level-n authorizing party system (APS-n). MIC-n is linked to lower level MIC-0 to MIC-(n−1). The vetting system, as level-n relying party system (RPS-n), uses the verified subject information associated with the linked MIC-0 to MIC-n to verify or not verify the identity of the subject, develops an identity profile of the subject, and determines a vetting result of the subject by calculating a composite trust score based on MIC trust values for the multiple levels of MIC. MIC-i (i=1 to n) is linked to MIC-(i−1) which UMD received from APS-(i−1), and APS-i is RPS-(i−1) which verified the identity of the subject using verified subject information associated with MIC-(i−1), such that MIC-0 to MIC-n are linked.

This disclosure provides systems, methods and apparatuses for identifying fraudulent accounts associated with an electronic payment service. In some implementations, a computing device may retrieve a data set including a number of attributes for each of a multitude of accounts, and may construct a plurality of different graphs each based on a unique set of the attributes. Each graph may include a plurality of nodes linked together by a multitude of edges, where each node identifies a corresponding account and each edge indicates one or more of the corresponding attributes that are common to a pair of accounts. The computing device may determine a likelihood of each graph correctly identifying fraudulent accounts by analyzing groups of nodes connected to each other by corresponding groups of edges using historical account data, and may select the graph having the greatest determined likelihood to predict whether any of the accounts is fraudulent.

A method of predicting crop yield includes generating, via a processor, a plurality of vectors representative of growing conditions for a current time period and a plurality of vectors representative of growing conditions for a previous time period. The processor compares the plurality of vectors for the current time to the vectors of the previous time periods for corresponding growing conditions and determines which previous vectors are closest to the current vectors. The plurality of previous time periods are each associated with crop yields. Thus, the processor can determine a crop yield for the current time period for a selected crop producing field and crop type based on crop yields for the closest previous time periods.

Disclosed is a system and method for verifying the authenticity of goods for sale. The system includes an authenticity device on the product which determines a code using a two step authenticity algorithm which inputs time as a variable and outputs the code. The code may be displayed on the authenticity device. The smart device contacts the manufacturer via an application and a wide area network and provides identification information regarding the product. Based on the identification information, the manufacturer finds the copy of the authenticity algorithm stored at the manufacturer, runs the algorithm, and returns the code to the smart device.