Embodiments described herein are directed to computer-implemented methods, systems, and computer program products for calculating a metric using natural language processing tokens. A non-limiting example of the computer-implemented method includes parsing, by a processing device, user content using a natural language processing technique to extract tokens. The method further includes filtering, by the processing device, the tokens relating to a natural language processing criterion. The method further includes calculating, by the processing device, a metric based at least in part on the filtered tokens. The method further includes determining, by the processing device, whether to take an action by applying the metric to a set of rules. The method further includes taking the action responsive to determining to take the action.

Systems and methods are disclosed that provide for a linking of a product database across different search platforms and then managing payments by a generalized search entity such that users are not transitioned to a merchant site from advertisements or search results. A method includes establishing, at a generalized search entity, a link to a product database of a merchant, offering, by the generalized search entity and based on a correlation of search terms to the product database of the merchant, search results across at least a first search platform and a second search platform and receiving, from a user, a confirmation of a payment for a product associated with a search result presented on the first search platform by the generalized search entity. The generalized search entity processes the payment for the product without transitioning the user to a site operated by the merchant.

Systems and techniques for context aware predictive activity evaluation are described herein. A set of transaction variables may be identified for a predicted transaction. A set of inputs may be obtained corresponding to each transaction variable of the set of transaction variables. A value may be determined for each transaction variable using the set of inputs corresponding to each transaction variable of the set of transaction variables. The value for each transaction variable may be compared to a set of transaction models to select a transaction model for the predicted transaction. A probability may be calculated that the predicted transaction will be approved using the transaction model for the predicted transaction. The probability that the predicted transaction will be approved may be displayed on a display device.

Disclosed are methods, systems, and non-transitory computer-readable medium for analysis of images including wearable items. For example, a method may include obtaining a first set of images, each of the first set of images depicting a product; obtaining a first set of labels associated with the first set of images; training an image segmentation neural network based on the first set of images and the first set of labels; obtaining a second set of images, each of the second set of images depicting a known product; obtaining a second set of labels associated with the second set of images; training an image classification neural network based on the second set of images and the second set of labels; receiving a query image depicting a product that is not yet identified; and performing image segmentation of the query image and identifying the product in the image by performing image analysis.

Systems and methods are disclosed for visualizing products in a single-page application. Consistent with disclosed embodiments, an application system can receive from a client system, during rendering of a webpage received by the client system from a host system, a request for a script associated with the host system. The script can be executable by the client system to perform operations including modifying the webpage to include a visualization application in response to a selection of a visualization control in the webpage by a user of the client system. Consistent with disclosed embodiments, the application system can receive, from the visualization application, a request to display a product in a first image. A location can be identified in the first image using a machine learning model. Instructions can be provided to the visualization application for displaying the product at the location.

A system is provided that includes a server having a first engine, a second engine, a search word warehouse, and a purchasing engine. The first engine (i) maps topics to product features of products using a topic hotness method which computes a hotness degree of a product on a topic from (a) product identifiers, (b) product features, (c) customer comments, and (d) topics with relevant key words, and (ii) builds a model providing a relevance degree of a topic to a product feature. The model is built based on the hotness degree. The second engine extracts remarkable topics based on product features using a method applied to the relevance degree of the topic to the product feature to identify remarkable topics for each product. The search word warehouse stores the remarkable topics for each product. The purchasing engine conducts purchases of products identified in searches using the remarkable topics.

Systems and methods for generating, administering and analyzing a user experience study are provided. In particular, intents can be generated from a user experience study by applying one or more screener questions to participants and subjecting the screened participants to one or more tasks. Corresponding clickstreams and success data for each participant engaging in the tasks can be recorded. The success and clickstream data can also be aggregated for all the screened participants as aggregated results. Video data including audio for each of the screened participants can also be recorded.

Systems and methods are described for dynamically updating the floor plan of a retail store, and for associating retail transactions with particular mobile devices, based on detection and attribution of foot traffic within the store. A foot traffic attribution system detects mobile devices accessing a wireless network. The foot traffic attribution system uses information obtained from the mobile devices to determine foot traffic data, such as locations of mobile devices relative to item display areas, direction of travel of mobile devices, durations of time spent in various areas, and similar information. The foot traffic attribution system then attributes the foot traffic data to items on display and/or item display areas in the current floor plan, and determines an updated floor plan. The foot traffic attribution system may also access retail transaction data, and may use the foot traffic data to associate retail transactions with particular mobile devices.

Systems, methods, and devices are disclosed for authenticating and predicting the remaining lifetime of a resold product. Telemetry data is received from a transceiver within the product, which is then stored within a distributed ledger. The lifetime of the product is determined by analyzing the telemetry data in the distributed ledger according to one or more models. In response to receiving a query about the product, the user is granted read access to the distributed ledger, including read access to the determined lifetime of the product and the authentication of the product (in real or near real time).

Disclosed are a system and process of providing social networking purchasing processes. A method includes receiving, from a posting entity and at the social networking entity, a posting or a submission of a text, an image or a video. When the submission is associated with a product within a product catalog of the posting entity, the social networking entity presents in a newsfeed of users or otherwise on the social networking entity, the text, image or video with an associated option to buy. The option to buy might be presented through a messenger application or as the user browses the posting. When there is a correlation between the posting and the product catalog, and when the user makes a purchase of the product, the user is not transitioned away from the social networking entity. Initiating a payment process occurs within the social networking entity.