A computer-implemented method and system for streamlining interactions between a customer and a customer service representative of a company. An interaction is commenced between the customer and the customer service representative during which historical data is accessed related to the customer stored in a company controlled computer system responsive to the interaction. The historical data preferably relates to at least one product or service provided by the company to the customer. At least a part of the historical information is displayed to the customer service representative. On the display, a first tab is generated related to the historical data as is a second tab relating to a quote for a new product or service for offering to the customer. The customer service representative is thereafter enabled to switch between displaying the historical data and the quote by selecting the first or second tab, respectively, without having to save the quote.

Methods and apparatuses are provided for use in monitoring product placement within a shopping facility. Some embodiments provide an apparatus configured to determine product placement conditions within a shopping facility, comprising: a transceiver configured to wirelessly receive communications; a product monitoring control circuit coupled with the transceiver; a memory coupled with the control circuit and storing computer instructions that when executed by the control circuit cause the control circuit to: obtain a composite three-dimensional (3D) scan mapping corresponding to at least a select area of the shopping facility and based on a series of 3D scan data; evaluate the 3D scan mapping to identify multiple product depth distances; and identify, from the evaluation of the 3D scan mapping, when one or more of the multiple product depth distances is greater than a predefined depth distance threshold from the reference offset distance of the product support structure.

A shopping cart system detects the initiation of a shopping session within a physical retail store by a customer, in which the shopping cart system includes a shopping cart, a processor, a memory, and a set of sensors. Contextual information associated with the shopping cart received by the sensors during the shopping session is tracked, in which the contextual information describes one or more locations of the shopping cart within the store, a state of the shopping cart, and a set of items within the shopping cart. Responsive to identifying an opportunity to present content to the customer based on the contextual information, the system identifies a set of content items associated with one or more items within the store based on the contextual information. The system generates a user interface including the set of content items and sends the user interface to a display area associated with the customer.

Systems and methods managing interaction between one of a plurality of advisors and a client. Client intent is determined based upon request details indicating a category of interest to the client. One of a plurality of advisors is selected to advise the client based, at least in part, upon the category and the client intent. The client is added to a sales pipeline of the selected advisor, and the selected advisor is prompted, at intervals, to interact with the client. The workload of each advisor is managed. The selected advisor is also prompted to generate and send a curation to the client. The systems and methods also provides e-commerce card fraud protection using conventional transaction processing methodology by including a random code in a pending transaction for the card and finalizing the transaction with the card provider when the code is correctly returned by the client.

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.

This disclosure provides systems, methods and apparatuses for recommending items to users of a recommendation system. In some implementations, the recommendation system determines a plurality of contribution values based on interactions between a plurality of users and a plurality of items. Each of the plurality of contribution values represents a confidence level that a respective user prefers a respective item. The recommendation system further determines a capacity of each of the plurality of items. The capacity of each item represents a maximum number of users to which the item can be recommended. The recommendation system recommends one or more items of the plurality of items to each of the plurality of users based at least in part on the plurality of contribution values and the capacities of the plurality of items.

A method for automatically updating a plurality of virtual shopping carts, includes receiving image data captured in a retail store, wherein a first shopping receptacle and a second shopping receptacle are represented in the received image data, determining that the first shopping receptacle is associated with a first virtual shopping cart and that the second shopping receptacle is associated with a second virtual shopping cart different from the first virtual shopping cart, analyzing the received image data to detect a shopper placing a first product in the first shopping receptacle and to detect the shopper placing a second product in the second shopping receptacle, automatically updating the first virtual shopping cart to include information associated with the first product, and automatically updating the second virtual shopping cart to include information associated with the second product.

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.

Methods, systems, and computer-readable media are provided for controlling a detail level of shopping data provided to frictionless shoppers. In one implementation, a method may comprise: receiving image data captured using one or more image sensors in a retail store; analyzing the image data to identify a plurality of product interaction events for at least one shopper in the retail store; determining shopping data associated with the plurality of product interaction events; determining a likelihood that the at least one shopper will be involved in shoplifting; based on the determined likelihood, determining an update rate for updating the at least one shopper with the shopping data; and delivering the shopping data to the at least one shopper at the determined update rate.

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.