An acquirer acquires last date information and at least one of frequency information and money amount information. The last date information indicates a last store visit date when a customer last visited a store or a last purchase date when the customer last purchased a product at the store. The frequency information indicates at least one of a frequency with which the customer has visited the store and a frequency with which the customer has made a purchase at the store. The money amount information is information about an amount of money of products purchased by the customer at the store. A product selector selects a product whose advertisement is required to be presented to the customer using at least one of the frequency information and the money amount information. On the basis of the last date information, an information amount determiner sets a condition.

Systems for a personalized Uniform Resource Locator (URL) encoded for full chain-of-attribution enabling exponential growth marketing are disclosed. Some embodiments may include: generating a personalized Uniform Resource Locator (URL) for a creator, the personalized URL being encoded for full chain-of-attribution by being specific for the creator, the personalized URL comprising a protocol, an Internet Protocol address, and a sub-directory, the sub-directory being specific for the creator, providing the personalized URL to the creator for sharing with a plurality of followers of the creator, receiving registration data of click inputs by the plurality of followers on the personalized URL, generating a destination Uniform Resource Locator based on the click inputs by the plurality of followers on the personalized URL, the destination URL being encoded for the full chain-of-attribution by being specific for the creator and specific for a destination.

A method for associating a device with a user including the action of receiving from a first computerized device operated by a first user a first data content including a plurality of first data items, including clickstream data. An action of setting rules for computing scores representing similarity between a first data item received from the first computerized device and a second data item received from a second computerized device. An action of collecting the plurality of the first data items and the second data items, from the plurality of computerized devices of the plurality of computerized devices. An action of computing the score representing similarity between at least one pair of computerized devices respectively providing the first and the second data items. And an action of determining that the pair of computerized devices are operated by a same user if the score reaches a predetermined value.

One or more videos are presented to a user. The videos include a plurality of hidden artifacts. The videos also include advertisements. The user looks for the hidden artifacts in the videos. Whenever the user finds the hidden artifacts in one of the videos, the user selects locations in the videos that correspond to the hidden artifacts. A computing device performs different actions depending on which ones of the hidden artifacts the user is able to find. For example, the computing device can provide different rewards to the user depending on which ones of the hidden artifacts the user is able to find.

This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

In general, techniques are disclosed to facilitate communicating within computer networks. For example, a layer three (L3) router including a service card and an interface card may be configured to perform the techniques. The interface card receives a query from a network that sources communications in accordance with a plurality of models. The query may specify a customer device and one of the sourced communications, and request that the service card select one of the models for the specified sourced communication and the specified customer device. The service card further stores data defining a profile for the one of the customer devices. The service card may also, in response to the query, analyze the profile data for the specified customer device to determine the selected one of the models for the specified sourced communication with respect to the specified customer device.

Methods and systems to identify a user across multiple browsers and machines are described. In some embodiments, a web request is received at a retrieval service from a browser. The web request may include a request to access a retrieval service website of the retrieval service and may be initiated by a redirection of the browser from a requesting service to the retrieval service. A unique identifier associated with a user logged in to an account of the retrieval service may be determined. The user may be logged in to the account via the browser. A redirect request is sent from the retrieval service to the browser. The redirect may include the unique identifier and may redirect the browser from the retrieval service website to the requesting service. The unique identifier may be used by the requesting service to perform additional functionality specific to the user.

Various arrangements for detecting items in home are presented. Imaging devices may capture images of a user's home. The images may be analyzed and compared against a user approved list of item definitions. Using the definitions, items, brands, trademarks, and the like may be identified in the images. The items identified in the images may be used to determine preferences of a user and provide targeted marketing content using the television receiver. In some cases, analysis of items in a home may be used to determine the effectiveness of marketing content by determining causality or correlations between marketing content viewed by a user and items in the home.

A method, computer program product, and system to perform a sale transaction are provided. The method includes identifying each item of a plurality of items, based on at least one image of the plurality of items, determining a cost for each item, optionally identifying a person based on an image of the person, adding each of the items and each of the costs to a sale transaction, and charging the person for the sale transaction.

A computing device receives a message including a request for a recommendation. A representation of a hypothetical ideal recommendation to provide in response to the message is determined based on the message content. Data regarding entities that are potential recommendations are retrieved from a data store, the data regarding each entity including a representation of the entity (e.g., a vector) derived from factual information about the entity and opinions of other users of the entity. Ranking scores are determined for at least a subset of the entities based on the difference between the entity representations and the representation of the hypothetical ideal recommendation. An entity to recommend is selected based on the ranking scores and a reply to the message is sent that identifies the selected entity.