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 detect a shopper in the retail store; determining a likelihood that the shopper will be involved in shoplifting; controlling a detail level associated with frictionless shopping data provided to the shopper based on the determined likelihood that the shopper will be involved in shoplifting.

A transaction system has Internet-connected partner platforms which display webpages with an Offer-Now button initiating coded instructions to display an electronic input form enabling a person to configure a transaction offer, and an Internet-connected service enterprise providing the coded instructions to the partners, configured specifically to partner requirements. Upon the person activating the Offer Now button from a mobile device, a verification code is sent to the device, to be returned to verify the device, and offer input provided through the device and the electronic form is tracked to be saved as an offer for the transaction.

A customer order is received and associated with a list of items being ordered from an in-store counter of a store. An estimated time of preparing the order by attendants of the in-store counter is calculated. The customer selects a time to pickup the order after presented with the estimated required time to fulfill and prepare the order. The order is placed on behalf of the customer with the store. Status updates for the order are sent to the customer on a customer-operated device. Once the status of the order indicates the order is completed, the customer travels to the in-store counter within the store and picks up the order.

A system and method include a kiosk processor, a device kiosk on a customer mobile device, which displays via a user interface, content and options for the customer from a third party customer service system, a customer interaction channel that receives, via an associated customer interaction network, a request to access the third party customer service system, an authentication module associated with the kiosk processor that receives customer data and customer input associated with an authentication request to authenticate the customer, identifies a customer mobile device based on device identifiers, and evaluates risk factors associated with the customer mobile device, and a communication interface associated with the kiosk processor, that transmits, via a push notification gateway, a push notification to the device kiosk on the customer mobile device that establishes, via the network, a secure connection between the customer mobile device and the third party customer service system.

A user treatment engine uses user data describing characteristics of a user to evaluate a set of treatments that the user treatment engine may apply to the user. The user treatment engine generates treatment cost predictions for the treatments and generates treatment scores for the set of treatments based on the treatment cost predictions for the treatments and the user data for the user. The user treatment engine selects and applies a treatment from the set of treatments based on the generated treatment scores. The user treatment engine determines a reward to the online concierge system for the application of the treatment to the user and updates treatment selection parameters for the applied treatment based on the determined reward.

A method and a system to present samples of products to customers by transporting the samples to the customer's location with an autonomous vehicle. The sample can be a product, a component of a product, a material or a device to gather information in defining the product. The autonomous vehicle is adapted for off road travel and may enter buildings, it can be carried to a nearby location by a street adapted vehicle. Information may be transmitted electronically but physical presence is essential. The customer or the customer's agent receives a presentation of the product definer and a selection of a final product is made. In other cases the autonomous vehicle delivery separate or installed technical equipment to examine the presentation location and assist in the final product selection. For example, photographs from multiple locations can measure a room for installation of carpets or draperies, etc.

A method for identifying products removed from bulk packaging includes receiving one or more images acquired by a camera arranged to capture interactions between a shopper and one or more bulk packages each configured to contain a plurality of products, analyzing the one or more images to identify the shopper and a particular bulk package among the one or more bulk packages with which the identified shopper interacted, receiving an output from at least one sensor configured to monitor changes associated with the particular bulk package, analyzing the output to determine a quantity of products removed from the particular bulk package by the identified shopper, and updating a virtual shopping cart associated with the identified shopper to include the determined quantity of products and an indication of a product type associated with the particular bulk package.

An online concierge system uses a new treatment engine to score users for applying treatments of a new treatment type. The new treatment engine uses treatment models to generate treatment lift scores for the user. The new treatment engine applies an aggregation function model to the treatment lift scores to generate an aggregated lift score for the user. If the aggregated lift score exceeds a threshold, the new treatment engine applies a treatment of the new treatment type to the user. The new treatment engine trains the aggregation function model based on training examples used to train the treatment models. For a training example associated with a particular treatment type, the new treatment engine uses a target lift score generated by the treatment model for the treatment type to evaluate the performance of the aggregation function model, and to update the aggregation function model accordingly.

An agent selection component that selects and activates artificial agents for interacting with a user on behalf of various entity based on user interaction with a real environment. The agent selection component detects user interaction with the real environment, and evaluates the detected user interaction. Based on that evaluation, the agent selection component selects an artificial agent that acts for an entity from amongst multiple artificial agents that act for different entities (e.g., to answer questions, to place orders, to schedule, or the like). The agent selection component then causes the selected artificial agent to activate to interact with the entity. Thus, different interactions with a real environment may result in the agent selection component permitting the user to interface with artificial agents for different entities.

A method and apparatus for a commerce platform coordinating a purchase of a product sold by a merchant system through a third party application are described. The method may include receiving a notification from the third party application requesting to purchase a product from within the third party application, wherein the notification comprises an identifier for the product and an identifier for the merchant system that sells the product. The method may also include a product checkout interface having an appearance consistent with an appearance of a user interface of the third party application, and transmitting the product checkout interface generated by the commerce platform to a user device executing the third party application causing the third party application to render the product checkout interface within at least a portion of the user interface of the third party application.