Some implementations disclosed herein measure an effect of content exposure (e.g., lift attributable to ad campaign content) by comparing exposed and unexposed conversion (e.g., visit) rates. The measurement processing is distributed between the computing systems used/controlled by different entities: a processing entity and a conversion data collection entity (e.g., a selling entity) so that identifier-level conversion data (e.g., user-level conversion data, device-level conversion data, household-level conversion data, etc.) does not need to leave the conversion data collection entity system(s).

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing conversion path performance measures and reports. In one aspect, user interaction data are obtained, were the user interaction data specify user interactions for a plurality of conversions. User interactions that are associated with each conversion are selected from the user interaction data, where the associated user interactions for each conversion are user interactions with a converting user during the conversion cycle for the conversion. Using the user interaction data for the selected user interactions, a quantity of user interactions that are associated with each conversion and occurred during the conversion cycle for the conversion are determined. In turn, conversion path performance measures are computed and reports specifying the conversion path performance measures are generated.

A method of assigning advertisements to slots in video channels of a bundle of channels provided to an end user. The method includes managing credits, for each specific channel of the channels, indicative of a difference between a number of advertisements provided by an owner of the specific channel that were displayed on other channels and a number of advertisements provided by owners of other channels displayed on the specific channel In addition, scores indicative of a predicted success of the advertisement with the end user are calculated for a plurality of advertisements. An advertisement to be displayed to the end user is selected responsive to a function of both the calculated scores and the managed credits.

The present disclosure provides a computer-implemented method and system for running high performance marketing campaigns for granular-level segments of users in real-time. The computer-implemented method and system corresponds to a user segmentation system. The user segmentation system receives a first set of data associated with a plurality of users. The user segmentation system fetches a second set of data. The user segmentation system obtains a third set of data. The user segmentation system analyzes the first set of data, the second set of data and the third set of data. The user segmentation system enables segmentation of the plurality of users. The user segmentation system assigns one or more segment goals. The user segmentation system creates a plurality of micro-segments. The user segmentation system triggers initialization of one or more marketing campaigns. The user segmentation system predicts performance of each of the one or more marketing campaigns.

The present disclosure provides a computer-implemented method and system for assessing an effectiveness of one or more marketing campaigns using RFM matrix in real-time. The computer-implemented method and system corresponds to a marketing campaign evaluation system. The marketing campaign evaluation system receives a first set of data. The marketing campaign evaluation system fetches a second set of data. The marketing campaign evaluation system obtains a third set of data. The marketing campaign evaluation system analyzes the first set of data, the second set of data and the third set of data. The marketing campaign evaluation system enables segmentation of a plurality of users in one or more segments. The marketing campaign evaluation system initiates the one or more marketing campaigns through a RFM grid. The marketing campaign evaluation system creates a transition representation. The marketing campaign evaluation system evaluates the effectiveness of each of the one or more marketing campaigns.

A system for processing information requests associated with mobile devices comprises an evaluation module configured to determine at least one performance measure for each of a plurality of information documents using at least data in one or both of a requests database and events database. The at least one performance measure includes at least one of an impression-based performance measure, a click/call-based performance measure, and an off-line site-visit-based performance measure. The system further comprises an information server configured to select a first information document for transmitting to a first mobile device to fulfill a first request. The information server includes a volume control unit configured to derive an off-line site visit projection in response to the first document being selected based at least in part on an off-line site-visit-based performance measure and having been impressed on the first mobile device, and to adjust a budget associated with the first document using the off-line site visit projection.

A method includes receiving, from a computing device, a request for content hosted by a content provider and determining one or more experiment variations for the requested content that the computing device is assigned to based, at least in part, on the request. The method further includes generating, by a processing device, a hash value of the one or more experiment variations and transmitting the hash value to the computing device and to a caching server.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, to improve the impact of digital media. One of these methods includes providing a non-affiliated advertisement to a plurality of users. The method includes receiving indications that a subset of the plurality of users have viewed the non-affiliated advertisement. The method also includes creating a control group for an advertisement from the subset of the plurality of users that received the non-affiliated advertisement.

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.

Described are systems and methods that utilize ad campaign acquisition information and user profile data to probabilistically determine which users were acquired through which ad campaign. For example, a user probabilistic attribution score may be determined for each ad campaign for each user, and a user lifetime value may be allocated to different ad campaigns based at least in part on the determined probabilistic attribution scores.