This specification describes technologies relating to inferring interactions with advertisers. In general, one aspect of the subject matter described in this specification can be embodied in methods that include providing an online advertisement to a system, receiving data from the system indicating an interaction of the system with the online advertisement and data indicating a subsequent interaction of the system with an online resource of an advertiser associated with the online advertisement, and inferring that an advertisement conversion has occurred based on the received data. Other embodiments of this aspect include corresponding systems, apparatus, and computer program products.

Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of creating a unique identification (UID) for an online advertisement for an item available for sale from an online retailer, publishing the online advertisement with the UID for the item in an online medium of the online retailer, receiving a user selection of the online advertisement with the UID, coordinating displaying a landing webpage for the item from the online retailer on an interface of the user electronic device, recording the user selection of the online advertisement with the UID in an event log, and extracting the UID from the event log to track clicks of the online advertisement when published.

A method and system for providing network based target advertising and encapsulation having a method for targeting advertising. When no ad in the inventory at the right of first refusal ad server is appropriate to the determined demographic, the method includes: identifying the content server at the right of first refusal ad server based on the ad request; determining a default ad server based on the identified content server, the default ad server being independent, separate, and distinct from the right of first refusal ad server; sending a pass request from the right of first refusal ad server to the default ad server; forwarding the ad request from the content server to the default ad server in response to the pass request; and serving a default ad service ad from the default ad server to the user node in response to the forwarded ad request.

Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, for providing content. A method includes receiving a request for an advertisement to be displayed in a slot associated with a third-party content site; identifying a relevant advertisement to be provided in the slot; determining information to be included in an annotation associated with the advertisement, the annotation including customized information to be presented along with the advertisement; providing the advertisement responsive to the request including providing the annotation along with a control for re-publishing the advertisement along with the relevant advertisement; receiving user input selecting the control and designating the advertisement for re-publishing to a group, the group being designated by the user; and targeting additional content to the group based on the received user input.

A method for enabling a user to view information filtered to align with the user's life state includes enabling the user to register and become a member of an information delivery system. The user provides the information about the user's life state. This information may include at least demographic information, ethnic information, social information and psychological information. The user may grant partners permission to access the information about the user's life. The granting of the permissions is performed and controlled by the user and may be limited to some information about the user's life. The partners are also members of the information delivery system. The partners are evaluated using a set of criteria before they become members of the information delivery system. The partners may use the information about the user's life to filter its information according to the information about the user's life. The method also enables the partner to participate in a marketplace to procure the information about the user's life, to rate the user according to the user's behavior, and to enable search engines to filter search results according to the information about the user's life.

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.

Data for a plurality of entities that can be offered a plurality of products can be obtained. The data can include categorical data and numeric data. Based on business constraints, some of all of the data can be selected. The selected data can be converted to another set of numeric data, wherein the categorical values are converted to numeric values. Dimensions of the converted data can be reduced to generate another set of data. Based on this another set of data, clusters of entities can be formed. The products can be grouped by assigning a unique product identifier of each product to a corresponding cluster. This grouping of products can be used by a predictive model to predict a likelihood of an entity to purchase a particular product in a future time period. Related methods, apparatus, systems, techniques and articles are also described.

The systems and methods may be used to recommend an item to a consumer. The methods may comprise determining, based on a collaborative filtering algorithm, a consumer relevance value associated with an item, and transmitting, based on the consumer relevance value, information associated with the item to a consumer. A collaborative filtering algorithm may receive as an input a transaction history associated with the consumer, a demographic of the consumer, a consumer profile, a type of transaction account, a transaction account associated with the consumer, a period of time that the consumer has held a transaction account, a size of wallet, and/or a share of wallet. The method may further comprise generating a ranked list of items based upon consumer relevance values, transmitting a ranked list of items to a consumer, and/or re-ranking a ranked list of items based upon a merchant goal.

Electronic correspondence that includes one or more promotions may be generated for presenting to a consumer. In order to determine whether to present the electronic correspondence to the consumer, the promotions included in the electronic correspondences may be analyzed in terms of a probability the consumer will accept the promotions, a relevance level between the promotions and attributes of the consumer, a relevance level between the promotions and the consumer, a relevance level between the promotions and a set of goals or rules, among other similar terms. After the analysis, a determination may be made whether to send the electronic correspondence to the consumer. Similarly, the analysis may compare multiple electronic correspondences, and determine, based on the comparison, which of the multiple electronic correspondences to send to the consumer.

Systems and methods of dynamically varying the intensity of providing content items in a remarketing campaign based on tracking client device interactions are provided. The system can assign an account identifier to a first segment for a pre-conversion model, responsive to receiving a first interaction associated with a content provider from a client device. The system can assign the account identifier to a second segment for the pre-conversion model, responsive to receiving a second interaction. The system can assign the account identifier to a third segment, responsive to receiving a third interaction. The third interaction can include a conversion event. The system can generate a post-conversion model based on the third segment and the pre-conversion model. The system can determine an intent index for the account identifier based on the post-conversion model. The system can store the account identifier into an interest cluster based on the intent index.