Systems, methods, and computer-readable media are described for creating custom user interface (“UI”) controls. A networked computing service may determine that an action performed by a user of the service is likely to be repeated, based on previous actions performed by the user and/or other users, parameters of the action including characteristics of an item associated with the action, and other criteria. The networked computing service may generate, or recommend generation of, a custom UI control that automates performance of the action. The networked computing service may automatically determine parameters of the action, and may determine alternative parameters and/or alternative actions if the action cannot be performed using the determined parameters. Custom UI controls may be associated with various computing devices and/or other electronic devices, and categories of custom UI controls may be determined and displayed.

Systems, methods, and computer program products for identifying a relevant candidate product in an electronic marketplace. Embodiments perform a visual similarity comparison between candidate product image visual content and input query image visual content, process formal and informal natural language user inputs, and coordinate aggregated past user interactions with the marketplace stored in a knowledge graph. Visually similar items and their corresponding product categories, aspects, and aspect values can determine suggested candidate products without discernible delay during a multi-turn user dialog. The user can then refine the search for the most relevant items available for purchase by providing responses to machine-generated prompts that are based on the initial search results from visual, voice, and/or text inputs. An intelligent online personal assistant can thus guide a user to the most relevant candidate product more efficiently than existing search tools.

Disclosed is a method including presenting an input field on a user interface of a generalized search entity, wherein the generalized search entity processes data using a generalized search engine that indexes and searches both merchant sites and non-merchant sites, receiving user input in the input field and determining whether the user input corresponds to a product in a product database to yield a determination. When the determination indicates that the user input does correspond to the product in the product database, the method includes presenting a purchase-related search result, wherein the purchase-related search result is configured such that when a user interacts with the purchase-related search result and confirms a purchase associated with the purchase-related search result, the generalized search entity initiates a purchasing process for the product.

Disclosed are systems, methods, and non-transitory computer-readable storage media for semi-opaque sales with bundles of items. An example bundle can include hotel lodging and a bonus service, status, or item associated with that hotel. An system can identify a first bundle of a first base and bonus item, and a second bundle of a second base and bonus item. The system can present a semi-opaque offer comprising the first bundle, the second bundle, and a discount price, wherein the semi-opaque offer does not identify which of the first bundle and the second bundle will be sold at the discount price to the user upon acceptance of the semi-opaque offer, and wherein the discount price is a full price of the first base item. After receiving acceptance of the semi-opaque offer from the user, the system can disclose that the user has purchased the first bundle at the discount price.

A method for three-dimension (3D) based shopping, the method may include receiving or generating a 3D representation of at least a part of a body of a certain customer; receiving a query to find a first wearable item that fits the part of the body; searching for the first wearable item; displaying on a display that is accessible to the certain customer a 3D model of the first wearable item when worn over the part of the body; and interacting with the certain customer till a completion of the 3D based shopping.

There is provided a program, an information processing apparatus, and an information processing method which are able to represent a demand-supply balance that reflects a characteristic of a transaction object, more accurately. The program causes a computer to function as a control unit that, on the basis of inputted transaction orders, controls a display regarding a distribution of the transaction orders in a transaction market, where the transaction orders include a provision order inputted by a provider who desires to provide a transaction object and a reception order inputted by a receiver who desires to receive the transaction object, and the control unit dynamically controls the display regarding the distribution on the basis of two or more elements including a desired transaction price related to each of the provision order and the reception order and including at least one or more characteristics of the transaction object.

A computer implemented method of image analysis is disclosed. The method comprises receiving, from a first computing device associated with a first human user, a communication indicating that the first human user has selected one or more items for purchase and has purchased the items; receiving, from the first computing device, identifying information of the items; identifying one or more merchants offering the items for sale; receiving one or more images depicting the first human user using the items; after receipt of the images, automatically determining, based on visual characteristics of the images, that the items are depicted in the images; and transmitting, for display to the second human user, an automatically generated augmented graphical user interface comprising the images and hyperlinks that convey the second human user to a merchant website allowing the second human user to purchase the items from the merchants.

One aspect of the present disclosure is directed to a computer-implemented method for streamlined product searching. The method may include receiving a search query comprising at least one keyword; generating a listing of related products based on the keyword; ranking each related product based on applicability; determining a product type of at least the highest ranking related product; determining a filter sequence associated with the product type; generating a first record comprising the filter sequence; instantiating a second record of selected attributes; displaying a first filter in the filter sequence; receiving a first selected attribute from the first filter; displaying the second filter; receiving a second selected attribute from the second filter; and displaying a listing of products associated with the selected attributes in the second record.

Integrating an image capturing mechanism into an ecommerce application is described. Images of items offered for sale via ecommerce channels associated with an ecommerce service provider and performance metrics associated with the images and/or content items with which the images are presented via the ecommerce channels can be analyzed. Based partly on the analyzing, a characteristic associated with the images that are associated with a performance metric that satisfies a threshold or that are presented by the content items that are associated with the performance metric that satisfies the threshold can be determined. A new image of an item to be offered for sale by a merchant via an ecommerce channel can be received and, based at least partly on the characteristic, it can be determined whether to integrate the new image into a content item for the merchant, wherein the content item to be presented via the ecommerce channel.

An online system provides options for selection by a user. The online system receives a query entered on a client device. The online system queries an item database to retrieve a set of items related to the query and assigns each item to a product category in a predefined taxonomy that maps items to product categories. The online system inputs each item into a prediction model trained to predict a probability that an item is available at a warehouse location. The online system determines that a first product category has low availability based on predicted probabilities for items in the first product category. Responsive to determining that a first product category has low availability, the online system generates a generic item for the first product category and sends a list of items including the generic item to the client device for display responsive to the query.