Multiple users of a household can each have a different profile associated with a common account for an online concierge system. This association of different profiles with the common accounts allows the concierge system to show a user of the household what other users of the household purchased and rank items for suggestion to the user based one purchases of other users, facilitating order building. The online concierge system also enables a user profile to designate a user profile associated with the common account for an order pickup or as a contact for a home delivery. Additionally, association of different user profiles with the common account may be used for account recovery of one of the user profiles. Further, different user profiles may have different permissions for creating an order with the online concierge system.

Traditionally, strategies are carried out based on customer intention indicated from surveys, transactional data, location of the store and customer profile. They have limitations such as partial capture of customer intention, absence of transactional data, challenges in defining catchment area associated with store location and lack of customer profiles. This disclosure relates to determining unified user intention from digital environment for plurality of strategies. An information associated with user is received. The information associated with the user is processed to derive weights associated with the user. The weights are integrated and mined through a variable reduction technique to determine at least one significant latent variable from a plurality of significant latent variables and associated significant attribute values. A structural equation model (SEM) is developed by applying the significant latent variables and the at least one event and a plurality of strategies are recommended for the plurality of applications.

Provided is a method of determining an advertisement target according to an advertisement request, the method includes: obtaining usage history information from a plurality of devices, obtaining features of the plurality of devices, based on the usage history information, and generating feature vectors for the obtained features; determining labels for the plurality of devices, based on the advertisement request and the obtained features; generating an advertisement target inference model, based on the determined labels and the feature vectors; and determining at least one advertisement target device among the plurality of devices by applying the generated advertisement target inference model to the plurality of devices.

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.

An online system for determining advertisements for retrieval is disclosed. The online system may assign a unique category path associated with a hierarchy of advertisement categories to a plurality of advertisements accessible by the online system to determine advertisement information features. The online system may determine a plurality of types of user engagements associated with prior user interactions by a user with one or more of the advertisements or types of advertisements associated with the advertisements to determine a set of user engagement features. The online system may select user engagement features, from the set, based on determined user engagement results to obtain user related features. The online system may associate the user related features with an assigned unique category path, associated with the ad information features, to generate inverted index features. The online system may apply the inverted index features as inputs to a neural network.

Systems and methods for targeted advertising to specific consumers are disclosed. A system may include a memory storing instructions; and at least one processor configured to execute the instructions to: receive, over a network, consumer data from a client device; identify a plurality of client-provided consumers from the consumer data; obtain a plurality of unique consumer identifiers corresponding to the plurality of client-provided consumers; and identify at least one first overlapping unique consumer identifier by matching at least one of the plurality of client-provided consumers with at least one publisher-provided consumer provided by a first publisher device of a plurality of publisher devices, the first publisher device having a highest priority among the plurality of publisher devices.

An online system accesses a model trained based on a topic associated with a set of content items and the content of the set of content items. The online system applies the model to predict a probability that each of multiple content items is associated with the topic based on its content and identifies (a) content item(s) associated with at least a threshold probability. The online system retrieves information describing user engagement with the identified content item(s) and determines a value of a performance metric for the topic based on this information. If the value is at least a threshold value and the online system receives content from an entity describing an item associated with the topic, the online system communicates a recommendation to the entity to create a content item describing the item and to add a tag associated with the item upon determining an opportunity to do so.

Aspects of the subject disclosure may include, for example, storing, in a database, information associated with a first item purchased by a user, the information comprising an identification of the first item and a time of purchase of the first item; receiving web browsing data based upon monitoring, by another device, web browsing of the user; determining, based upon the web browsing data that is received, whether the user is currently browsing at a shopping website, resulting in a determination; responsive to the determination being that the user is currently browsing at the shopping website, querying the database to determine an elapsed time since the time of purchase of the first item; responsive to the elapsed time meeting a threshold, generating a message to send to the another device monitoring the web browsing, the message informing the user of a suggested second item for the buyer to purchase, the suggested second item being a replacement for the first item; and sending the message to the another device for presentation to the user. Other embodiments are disclosed.

A system and method for tracking user activity across multiple advertising domains, including both off-site and on-site user activity. The present methods employ at least a first creative pixel associated with an ad exposure to obtain a unique ID for the user and capture user activity data associated with this unique ID. The unique ID assigned to the user is the same regardless of which advertising platform serves the ad. The present methods further employ at least a first site pixel associated with content provided by the advertiser to receive the unique ID for a visitor to the website which has previously been exposed to one or more advertisements on off-site websites. The use of a common unique ID for on-site and off-site activity, regardless of platform, enables sophisticated analytics of advertising performance across multiple advertising platforms.

Systems and methods for advertisement with a short message. In an aspect, after a user launches an app at a device, ads of nearby businesses show up. The ads each contain a name of a business and a short message from the business. In another aspect, ads provided for a user in a vehicle contain a name of a business, a short message from the business, a button for placing an order, and a button for driving the vehicle to the business.