Systems and methods are presented for standardizing delivery of products in an online marketplace using one or more locker systems. In some embodiments, a system of lockers is presented. The locker system may be configured to store one or more products sold in an online marketplace. The locker system may also include a processor coupled to the one or more lockers and configured to generate access code information for a buyer to enable access to a locker storing the product. One or more sensors may be coupled to the one or more lockers and configured to examine the product for a level of product quality. A transmitter of the system may be configured to transmit the access code information to the buyer. The system can later accept the access code information inputted from the buyer and open the locker storing the product after receiving the access code information.

A method and system for conducting an online payment transaction through a point of sale device. The method includes receiving input from a user selecting an item for purchase through the point of sale device; calculating a total purchase amount for the item in response to a request from the user to purchase the item; and sending payment authorization for the total purchase amount from the point of sale device to a payment entity, in which the payment authorization is sent to the payment entity via a mobile communication device of the user. The method further includes receiving a result of the payment authorization from the payment entity through the mobile communication device; and completing the payment transaction based on the result of the payment authorization.

Techniques are disclosed utilizing cognitive computing to improve commercial communications from vendors to users. A user's financial account(s) and location may be monitored to determine when a user is within a threshold distance of a vendor. If the user is within the threshold distance the methods and systems disclosed may determine which targeted commercial communications to transmit to the user based upon a shopping profile for the user. The shopping profile may include a dataset indicative of the shopping habits of the user.

An example apparatus includes processor circuitry to access demographics from a database proprietor corresponding to impression requests from computing devices indicative of media impressions, determine a first media impression count corresponding to a sum of first media impressions that occurred on first computing devices satisfying a device type criterion and that are attributable to a demographic group corresponding to a) the demographics from the database proprietor, b) panel-based demographics corresponding to a market segment, determine a second media impression count corresponding to second media impressions that occurred on second computing devices not satisfying the device type criterion and that are attributable to the demographic group corresponding to a) the demographics from the database proprietor, b) the panel-based demographics corresponding to the market segment, and determine a total media impression count by adding the first media impression count to the second media impression count that are attributable to the demographic group.

An automatic system facilitates selection of media properties on which to display an advertisement, responsive to a profile collected on a first media property, where a behavioral-targeting company calculates expected profit for an ad correlated with the profile and arranges for the visitor to be tagged with a tag readable by the selected media property. The profit can be calculated by deducting, from the revenues that are expected to be generated from an ad delivered based on the collected profile, at least the price of ad space at a media property where the BT company might like to deliver ads to the profiled visitor. When the calculated profit is positive (i.e., not a loss), the BT company arranges for the visitor to be tagged with a tag readable by the selected media property through which the BT company expects to profit.

Social media networking applications, web sites, and services creates implicit relationships between users based on their interest or participation in real-world and optionally virtual or online activities in addition to explicitly defined peer relationships. User profiles, activity entities, and expressions may be associated with metadata to assist in searching and navigation. Metadata is implicitly associated with user profiles, activity entities, expressions, or other data entities based on user behavior using metadata collector. A metadata collector is a poll, survey, list, questionnaire, census, test, game, or other type of presentation adapted to solicit user interaction. A metadata collector is associated with metadata elements. When users interact with a metadata collector, their user profiles and the data entities included in their interactions become associated with the metadata elements of the metadata collector. These metadata element associations may then be used for any purpose.

A method for simulating a social media account history may be provided. The method may include generating social media identification information (“social media ID”). The method may also include creating an account history for the social media ID with respect to a pre-determined entity. The creating may include identifying the social media ID with respect to at least one of a time-stamped indication of affinity for the predetermined entity. The creating may also include tagging of a photograph of the entity. The creating may also include linking of a photograph of the pre-determined entity. The creating may also include a threshold amount of streaming audio time relating to the predetermined entity. The method may also include querying the account history to determine whether the account history includes one or more parameters that indicate whether the social media ID information is related to an automated entity or a human entity.

Technologies for attributing purchases to a targeted marketing campaign include associating a captured payment card number and a captured cardholder identifier with a globally unique identifier. Additional payment card numbers related to the captured payment card number are associated with the globally unique identifier. A cardholder-specific marketing message associated with a targeted marketing campaign is transmitted to the captured cardholder identifier based on the globally unique identifier. The targeted marketing campaign is for an advertised product, which corresponds to a product identifier. A purchase transaction is attributed to the targeted marketing campaign in response to determining that a payment card number associated with the purchase transaction matches any of the payment card numbers associated with the globally unique identifier and determining that a product identifier corresponding to a purchased product of the purchase transaction is associated with the targeted marketing campaign. Other embodiments are described and claimed.

In one general aspect, a method can include identifying, by a computing device, a geographic proximity of an entity, establishing, by the computing device, direct short-range communications with the entity, the computing device and the entity being able to communicate with one another using a short-range communication protocol. The method can further include receiving, by the computing device, an indication that the computing device shares an identifier with the entity, and receiving, by the computing device, information relevant to the computing device regarding the entity based on the shared identifier.

Systems and methods directed to managing computer resource allocation by monitoring signals indicating demand for services utilizing computer resources are described. A method includes maintaining, for each first event of first events, historical registration data and respective parameter values of the first event and identifying, for a second event having an open registration status, respective parameter values of the second event, and registration data for the second event. The method includes computing a similarity score between the second event and each first event of the plurality of first events, based on the respective parameter values of the first event and the second event and the registration data of the second event and the historical registration data of the first event, generating, for the second event, a projected number of entities based on determined information and determining a ranking of the second event.