A multivariate testing platform is disclosed. The platform includes a test definition environment including a test deployment and data collection interface configured to (1) manage test deployments within a retail environment to a controlled subset of users across a plurality of content delivery channels, and (2) receive test data from an analytics server regarding user interaction regarding the test deployment. The test definition environment includes a self-service test definition and analysis tool configured to generate a user interface accessible by enterprise users, the user interface including a test definition interface useable to define a test selectable from among a plurality of test types and an analysis interface graphically displaying test results based on the test data from the analytics server.

Methods and apparatus to associate transactions with media impressions are disclosed. An example method includes transmitting a request for commercial transaction information to a database proprietor, the request including an identifier corresponding to a media impression associated with media presented via a computing device; receiving the commercial transaction information in response to the request, the commercial transaction information comprising data associated with a commercial transaction conducted using an account accessed by the computing device; and associating the media impression with the commercial transaction.

An operation system for media placement and income distribution includes a server and a media broadcast device. The server identifies a media placing end accessing the server and sends an information of rental fee. When the payment is complete, the server integrates the rental fee and calculates and distributes the rental fee to an income account of the server. The server allows the media placing end to transmit a media information through the internet, and the media information is transmitted to the media broadcast device. The media broadcast device is in the physical store for broadcasting the media information. Therefore, the media placing end promotes the media information to the people around the physical store. Also, the server provider and the physical store provider having the income account shares the rental fee. The cooperative benefit of the three parties are assured.

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium for dynamic contact information assignment. A method includes: identifying a pool of telephone numbers; assigning the telephone numbers to a pool manager; allocating by the pool manager, subsets of the telephone numbers to a plurality of allocators, each allocator responsible for allocating telephone numbers to an associated group of content sponsors; determining a first allocation of a first subset, the first allocation being distributed among the content sponsors associated with a first allocator, creating first pools each associated with a respective one of the content sponsors associated with the first allocator; reclaiming one or more telephone numbers from a pool of the first pools; and assigning ones of the reclaimed telephone numbers by the first allocator into either other pools of the first pools or back to the pool manager for allocation to other allocators.

A method and article of manufacture are provided for detecting message impressions from a document. The document includes one or more data collection areas adapted to receive input, and one or more message areas. Each message area includes a message. Memory representations of messages are stored in a memory. The document is received at a document processing engine which is adapted to access the memory to obtain the representations of messages. Message impressions are detected from the document by analyzing the document in the document processing engine. Message impressions are detected if it is determined that there is relevant input in the one or more data collection areas, and the document includes a representation of one or more of the messages.

Matching conversions from within applications on a client device to interactions with content items presented with resources may include receiving first data associated with an interaction with a content item displayed with a resource. The first data includes an application identifier for an application associated with the content item and an account identifier. The matching may also include receiving second data from the client device associated with a conversion using the application. The second data includes the application identifier and a device identifier for the client device. The matching may further include receiving third data from the client device that includes the account identifier and the device identifier. The conversion can be determined as associated with the interaction with the content item displayed with the resource based on matching the second data with the first data based on the third data.

In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers. In embodiments, predictive models based on gross revenue may be optimized using promotion category-dependent price boosting.

A computer-executable method, a computer system and a non-transitory computer-readable medium are provided for launching application programs on a mobile computing device. The method includes receiving, at a promotion application program, user input selecting a first impression of a first promotion associated with a first product or service offered by a first merchant. The method includes using the promotion application program to initiate detection of a first application program installed on the mobile computing device, the first application program associated with the first merchant. The method also includes, in response to the user input, using the promotion application program to automatically launch the first application program on the mobile computing device.

Systems and methods for verifying an advertisement impression in a digital environment are provided. In some aspects, methods of the subject technology include operations for defining a portion of the digital environment as an impression area, wherein the impression area is associated with a tagged advertisement area, providing a stream of an advertisement to the tagged advertisement area, and updating advertising impression information stored in memory regarding the advertisement, wherein an advertising impression is based on the identification of the character within the impression area and the availability of an unobstructed line-of-sight between the character and the tagged advertisement area. In some aspects, computer readable media are also provided.

At least one aspect is directed to determining an estimate of an intersection of user identifiers in a first set of user identifiers and a second set of user identifiers. The first and second sets of user identifiers can be populated with user identifiers that have interacted with the same content item or content item campaign. Estimates of intersections of the first and the second sets can be determined based on a binomial vector approach, a vector of counts approach, or a hybrid approach. The binomial vector approach generates vectors based on k hashes of each user identifier in the first set and summing the vectors to generate a first vector. The intersection can be determined based on a dot product of the first vector and a second vector similarly generated from the second set of user identifiers.