A method for addressing a shopper's eligibility for frictionless checkout may include identifying at least one shopper in a retail store designated as not eligible for frictionless checkout; in response to the identification of the at least one shopper designated as not eligible for frictionless checkout, automatically identifying an ineligibility condition associated with the at least one shopper's designation as not eligible for frictionless checkout; determining one or more actions for resolving the ineligibility condition; causing implementation of the one or more actions for resolving the ineligibility condition; receiving an indication of successful completion of the one or more actions; and in response to receipt of the indication of successful completion of the one more actions, generating a status indicator indicating that the at least one shopper is eligible for frictionless checkout and storing the generated status indicator in a memory.

A computing system facilities live and robo-advising sessions, and transitions therebetween based on detection of triggers. The computing system may extract voice inputs of a user from ambient sounds captured using a sound sensor. Based on an analysis of the voice inputs and detection of corresponding triggers, the computing system may initiate a robo-advising session, or a live communication session between a user computing device and an advisor computing device. Detection of another trigger during the robo-advising session or the live communication session may lead to a transition to a live communication session or a robo-advising session, respectively.

There is provided an air filter for use in a heating, ventilation, and air conditioning (HVAC) system, the air filter including: a front portion comprising a molded filtering material, the molded filtering material defining a plurality of pockets arranged over a front face of the front portion; and a rear portion joined to the front portion, the rear portion defining a plurality of holes therethrough. In another aspect, there is provided a method for determining performance of an air filter in a heating, ventilation, and air conditioning (HVAC) system, the method including: receiving a first temperature reading from a primary sensor measuring the temperature of return air in the HVAC system; receiving a second temperature reading from a secondary sensor measuring the temperature of supply air in the HVAC system; determining a temperature differential between the first temperature and the second temperature; outputting an indication of poor performance of the air filter where the temperature difference is greater than a predetermined value.

A method, system, and computer usable program product to determine a first mood of the user, where the first mood is based on a characteristic of the user at a first time during the providing of an online service and to determine a second mood of the user, where the second mood is based on a characteristic of the user at a second time during the providing of the online service. The first mood of the user and the second mood of the user are compared to determine a delta or change in mood of the user.

An electronic device has a display and a circuitry. The circuitry is configured to obtain location information of a specific item of multiple items located in an environment, wherein the location information of the specific item is obtained based on a correlation between location tracking information of electronic devices moving in the environment and item list data representing items of the multiple items being purchased by users of the electronic devices for which the location tracking information has been provided; and display an indication of the location of the specific item on the display.

A system and method are disclosed for accessing, by a computing device, a database that includes: business information representing a plurality of respective businesses that sell products and/or services to customers and customer information representing a plurality of respective customers, that purchase the products and feedback information representing submissions from the respective customers regarding experiences of the customers in connection with the respective businesses. Information associated with a sale of a product and/or service is processed including to associate a code with the sale. The customer is prompted to submit feedback information associated with the business and/or the sale of the product and/or service, and the feedback information is processed to store the feedback in the database and to provide the feedback information in a virtual guestbook associated with the business.

A system includes location indicators, a central computing system, and a mobile scanning device. The location indicators transmit location signals and are arranged in a store that includes stocked items. The central computing system stores an item association table that maps location values to the stocked items. The location values indicate locations of the stocked items in the store. The mobile scanning device receives ordered items from the central computing system, detects location signal(s), and determines a first location value based on the detected location signal(s). The mobile scanning device arranges the ordered items on a display based on the first location value, scans a first ordered item, and transmits data to the central computing system indicating that the first ordered item is associated with the first location value. The central computing system updates the item association table based on the data.

A system for determining whether shoppers are eligible for frictionless checkout is disclosed. The system has a processor that obtains image data captured using image sensors positioned in a retail store. The processor analyzes the image data to identify at least one shopper at one or more locations of the retail store. The processor detects, based on the analysis of the image data, at least one product interaction event associated with an action of the at least one shopper at the one or more locations of the retail store. Further, based on the detected at least one product interaction event, the processor determines whether the at least one shopper is eligible for frictionless checkout. In response to a determination that the at least one shopper is ineligible for frictionless checkout, the processor causes delivery of an indicator that the at least one shopper is ineligible for frictionless checkout.

Disclosed are methods, apparatus, systems, and computer readable storage media for interacting with components across different domains in a single user interface in an online social network. The user interface includes a first component and a second component, where the first component exposes content from a first database system at a first network domain and the second component exposes content from a second database system at a second network domain. A first interaction with the first component is received at a computing device, followed by a reference being provided in the second component, where the reference includes information related to the first interaction. A second interaction with the second component regarding the reference can be received at the computing device. Interactions between the components hosted on different database systems can occur through an application programming interface (API).

A system and method are presented for customer journey event representation learning and outcome prediction using neural sequence models. A plurality of events are input into a module where each event has a schema comprising characteristics of the events and their modalities (web clicks, calls, emails, chats, etc.). The events of different modalities can be captured using different schemas and therefore embodiments described herein are schema-agnostic. Each event is represented as a vector of some number of numbers by the module with a plurality of vectors being generated in total for each customer visit. The vectors are then used in sequence learning to predict real-time next best actions or outcome probabilities in a customer journey using machine learning algorithms such as recurrent neural networks.