Amazon Technologies, Inc.

Google Inc.

Lucas Paul Hansen

Sagnik Nandy

Evan Huang

Madhu Kallazhi Vasu

Luke Aron Snyder

Naomi Ben-Ayoun

Jerry Hong

Stella Marie Laurenzo

James Lee Wogulis

Paul Nicolas Muret

Bradley David Townsend

Neil Campbell Rhodes

Avi Mehta

Ashok Babu Amara

Nick Mihailovski

A tiered approach to selecting landing pages to be associated with specific keywords allows optimal landing pages to be determined dynamically and updated continually. Suggestions for landing pages can come from a number of sources based upon any of a number of factors. A scalable set of algorithms can be used to analyze these suggestions based upon factors including those used for determining the suggestions. Each algorithm can generate a decision as to an optimal landing page to be associated with each keyword. A subsequent algorithm can analyze each decision as these decisions relate to at least one goal, and can select an optimal landing page based thereon. A sponsored link or other element can be associated with the keyword such that a user submitting a request containing the keyword can be presented with the sponsored link to the optimal landing page.

Landing page selection for linked advertising

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

An advertiser submitting a sponsored ad to a provider can determine aspects of the ad, such as creative elements and bid price, based on a dynamic categorization of an item and/or landing page associated with the ad. An algorithm can be used that utilizes a browse tree for each item to be displayed to a user following a sponsored link, for example, and attempts to find a node in the browse tree that appears at the lowest level in the tree and with a sufficient appearance frequency. When consensus is reached for a node in the browse tree that meets these criteria, a corresponding categorization is determined, which can be used to determine appropriate aspects to be used for the sponsored ad, at least until enough information is obtained such that aspects can be determined independent of the categorization.

Dynamic categorizations for electronic advertising

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

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Seattle, WA, United States of America

Lucas Paul Hansen