Google Inc.

Sagnik Nandy

Chao Cai

Lik Mui

Gang Wang

Hui Sok Moon

Japjit Tulsi

Cameron Michael Tangney

Eric W Ewald

Matthew Robert Jones

Naomi Ben-Ayoun

David Allan White

Evan Huang

Paul Nicolas Muret

Madhu Kallazhi Vasu

Jerry Hong

Ashok Babu Amara

James Lee Wogulis

Jan Matthias Ruhl

Theodore Nicholas Choc

Bradley David Townsend

Lucas Paul Hansen

Neil Campbell Rhodes

Jonathon A Vance

Ognjen Nikolic

Elizabeth L Liebert

Yuan Zhuge

Avi Mehta

Nicholas John Seckar

Stella Marie Laurenzo

Wayne Douglas Vandermolen

Simon Wang

Brian Jonathan Patton

Ming Lei

Kasem Marifet

Robert A Walker

Jesse Savage

Zhimin He

Jieyan Fan

Liren Chen

Douglas VanderMolen

Niranjan Heddese Sitaram Shastry

Kevin Damm

Nick Mihailovski

Xiuduan Fang

Nagaraju Pothineni

Sissie Hsiao

Cedric Ho

The systems and methods described herein can enable the indirect transmission of session data between different domains. The system can pass the session data through a hashing function so that the data from a given domain remains private and secure to the specific domain. The system can generate clusters of associated domains for a given client device that the system can use to maintain a session between the client device and the domain.

Indirect transmission of session data

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for dynamically generating and configuring pre-aggregated datasets optimized for responding to particular types of data requests made against a large sub-optimal multidimensional dataset are disclosed. A dynamic aggregator monitors the query types and response latencies associated with queries made against the large multidimensional dataset. The dynamic aggregator defines pre-aggregated datasets based on the types of queries received from users and calculates a respective benefit score for each pre-aggregated dataset. The benefit score of each pre-aggregated dataset can be based on the recorded latencies and query count for the pre-aggregated dataset. The dynamic aggregator can decide whether to generate and/or maintain particular pre-aggregated datasets based on the current values of the benefit scores associated with the particular pre-aggregated datasets.

Dynamically generating pre-aggregated datasets

The subject technology provides configurations for propagating information from an initial analytics tracking data communication to subsequent analytics tracking data communications at an analytics server. In one example, the subject technology receives an analytics tracking data communication. The subject technology determines if the received analytics tracking data communication includes state changing information based on analytics tracking data included in the analytics tracking data communication. The subject technology then determines one or more attributes for propagating to subsequent analytics tracking data if the analytics tracking data communication includes state changing information. The state changing information are stored as one or more of the determined one or more attributes. The subject technology stores the analytics tracking data including the determined one or more attributes.

Persist and process analytics data dimensions for server-side sessionization

The present disclosure is directed generally to systems and methods for the server side matching of web analytics and content viewing. According to the methods and systems disclosed herein, a first identifier is delivered to a client device when the client device accesses a first website. If the client device later accesses of a second website the first identifier can be processed by the system to determine if the client device previously accessed the first website.

Server side matching of offsite content viewing to onsite web analytics data

Systems and methods for retroactively performing dimension widening on a data element are provided. A described method includes receiving a set of data elements from a database and a set of dimension widening rules. The method further includes identifying one or more of the data elements to which any of the dimension widening rules are applicable. The method further includes processing the identified data elements by applying the applicable dimension widening rules to the identified data elements. A dimension widening delta is generated for each data element, and the dimension widening deltas may be stored. The method further includes merging one or more of the data elements with one or more of the dimension widening deltas in response to a query.

Unlimited retroactive data element dimension widening

The subject technology provides configurations for providing aggregated analytics tracking data associated with a dynamically generated session in response to a query for analytics tracking data. A query for analytics tracking data associated with a period of time is received in which the analytics tracking data includes data for tracking activity associated with a web site or application. The subject technology determines analytics tracking data for aggregating according to the period of time in order to associate the aggregated analytics tracking data with a dynamically generated session. The aggregated analytics tracking data associated with the dynamically generated session is then provided in response to the query.

Dynamic sessionization of analytics data

A method and system for aggregating analytics data is discussed. The system differentiates between analytics data that is context sensitive and therefore cannot be reliably updated incrementally (e.g., unique page views, time on site, etc.) and analytics data that is not context sensitive. The system aggregates the context insensitive metrics and dimensions incrementally, while aggregating the context sensitive metrics and dimensions after a specified time duration, such as at the end of the day. It is estimated that less than 10% of all metrics and dimensions are context sensitive. In this way, the aggregator serveris able to improve the freshness of more than 90% of the analytics data (represented by the context insensitive metrics and dimensions) to a shorter period of time than the prior art. Further, this reduces the possibility of over-counting metrics.

System and method for aggregating analytics data

A method for sessionization of visitor activity includes receiving a first activity of a first client and a first client identifier from the first activity of the first client; the first client identifier stored at the first client; creating a first session from the first activity and the first client identifier; receiving a session link associated with the first activity; and creating a visitor-identified session based on the first client identifier, the first activity, and the session link.

Sessionization of visitor activity

Tracking data communications are received for single properties that include ambiguous event statistics. The event statistics are disambiguated by an analytics processing system by identifying account and visitor identifier pairs from account identifiers and visitor identifiers in the tracking data communications. For each account and visitor identifier pair, ambiguous event statistics are ordered by the corresponding event times and disambiguated.

Server side disambiguation of ambiguous statistics

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.

Conversion path performance measures and reports

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Los Gatos, CA, United States of America

Sagnik Nandy