Embodiments of the present disclosure provide methods, apparatus, systems, computer program products for supporting communication functionality in an interactive electronic technical manual system (IETM) configured to provide electronic and credentialed access via an IETM viewer to technical documentation for an item. In one embodiment, a method is provided comprising: providing a window comprising a communication session option; receiving input of a selection of the communication session option; responsive to receiving the input: identifying active users who are signed into the IETM for a particular object of the item based on credentials for the user and the user being signed into the IETM for the particular object; and causing display of an identifier for each active user on the window as selectable; receiving input of a selection of an indicator for an active user; and responsive to receiving the input, initiating a communication session with the active user within the IETM.

A system can visually track which items in a store are selected for purchase by a shopper. The system can form a virtual shopping cart by analyzing multiple images, over time, to determine which purchasable items are located with the shopper, such as in a physical shopping cart, in a basket, or held by the shopper. By analyzing multiple images, over time, the system can account for items misidentified in one or more images, or fully or partially obscured in one or more images as the shopper traverses the store. Alternatively, the system can form a virtual shopping cart by analyzing instances in which a purchasable item is removed from a shelf or placed on a shelf. Items removed from, but not returned to, a shelf can be considered to be selected for purchase. The system can include a frictionless checkout that charges the shopper for the selected items.

The method and system are directed at providing group purchasing at a historical price in an e-commerce environment. A user may select a price that a price at which a produce previous sold, seen as the historical price. This price may then be used to generate an online purchasing campaign that other user may join. The purchasing campaign is user or consumer driver rather than merchant driven.

In response to detecting that a first selectable element on a webpage or application page of a merchant has been accessed by a user, a computer system stores a visual representation of an item that corresponds to the first selectable element in a first space of the user. In response to detecting a selection of a second selectable element from within the first space, the computer system determines a threshold number of users to associate with the visual representation and creates a post in a network feed that includes the visual representation, wherein a third selectable element is associated with the post, that when selected, causes a user to join or vote for the first visual representation. In response to determining that a number of users that have selected the third selectable element meets the threshold number of users, the computer system initiates a group purchase for the item.

A system for obtaining user parameters of e-commerce users to auto complete checkout forms includes one or more processors configured to monitor user interactions of a user with a merchant website on a user device; determine an intent to purchase one or more items based of the monitoring; determine an unfilled template of a checkout form associated with the merchant website based on previously stored website information, wherein the unfilled template of the checkout form comprises a plurality of checkout form fields; determine one or more user parameters associated with the user device; apply a machine learning algorithm to predict a geolocation of the user device based on the one or more user parameters; and auto fill the at least one of the plurality of checkout form fields in the unfilled template of the checkout form based on the predicted geolocation.

Disclosed embodiments may include systems and methods for providing modified order recommendations. Line item data from a set of transactions associated with a vendor can be collected. The line item includes transactional data such as price, quantity, and frequency. The set of transactions are associated with a plurality of customers of the vendor. Correlations between line item data can be determined via one or more machine learning techniques to train a recommendation model. An order recommendation to a customer can be determine based on the correlations of the recommendation model. An order of the customer can be modified according to the order recommendation.

Methods and systems for inventory management and control. One aspect is a method for inventory management and control, the method comprising receiving and aggregating inventory data from a plurality of nodes in a retail enterprise, receiving scheduled inventory actions and at least one constraint definition, detecting at least one inventory issue cause by the at least one constraint definition, and adjusting, automatically, at least one scheduled inventory action of the scheduled inventory actions based on the at least one inventory issue.

Anchor points associated with point of sale information may be ordered by segmenting a trajectory derived from sensor data defined by adjacent turns to generate candidate links for each segment from which possible paths for the trajectory are derived. Each derived possible path may be scored with a multi-objective function using a global optimization algorithm to select a solution path from the derived possible paths that may be used to order a plurality of anchor points.

A method for an on-site purchase at an automated storage and retrieval system (ASRS) can include: analyzing likely impulse purchases for customers during a given season, the likely impulse purchases being associated with each customer's profile which comprises preferences, purchase history and search history; stocking items for customers to purchase and pick up at the ASRS, the stocked items comprising general and seasonal items, and supplementary items selected based on an analysis of the likely impulse purchases; receiving a customer's order for purchasing an item; detecting a customer's arrival within a predetermined area around the ASRS; offering a subset of the stocked items for the customer to add to the order, updating the order based on customer's purchase selections or declines; completing a payment transaction of the updated order; automatically updating the items for inclusion in the ASRS based on the customer purchase selections or declines.

Methods and systems for rendering lists of instructions and performing actions associated with those lists are described herein. In some embodiments, an individual may request that a voice activated electronic device associated with their user account assist in performing a task using a list of instructions. The list of instructions may include metadata that indicates actions capable of being performed by additional Internet of Things (“IoT”) devices. When the instructions are rendered, an instructions speechlet may recognize the metadata and may cause one or more of the IoT devices to perform a particular action. Furthermore, the metadata may also correspond to content capable of being rendered by the voice activated electronic device to assist the individual in performing a particular step of the instructions.