Google Inc.

Yahoo! Inc.

Bhavesh R Mehta

Kai Chen

James A Gallagher

Abhinay Sharma

Nicholas Charles Fox

Scott S Benson

Andrew E Silverman

Markus Mock

Mark Rose

Joerg Heilig

Dustin S Jackson

Wendy McKennon

Robert Kniaz

Dan Siroker

Benjamin A Hardy

Shalini Agarwal

Armin Ebrahimi

Xuefu Wang

Anurag Agarwal

Vibhor Nanavati

Michael David Bigby

Xinyu Tang

Angshuman Guha

Charles Chapin

Tomas Lloret Llinares

Shubhasheesh Anand

Nandakumar Ramani

Michael Clothier

An advertiser specifies a conversion-based bid for a conversion event associated with an ad. If a conversion event occurs for the ad, an effective conversion-based bid can be adjusted by a risk premium associated with the ad. An account associated with the advertiser can be debited based upon the adjusted effective conversion-based bid.

Risk premiums for conversion-based online advertisement bidding

Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, and including a method for providing content. The method comprises receiving a request for content from a user, the request for content being associated with a location and including one or more keywords. The method further comprises determining a prominent entity in proximity to the location and one or more categories associated with the prominent entity. The method further comprises evaluating historical search queries received from the user to determine one or more interests of the user. The method further comprises determining one or more additional keywords based on the evaluating. The method further comprises determining one or more content items based at least in part on the one or more keywords, the categories and the one or more additional keywords. The method further comprises providing the one or more content items responsive to the request.

Interest-based keywords for prominent entity and by location

Methods, systems, and apparatus, including computer program products, that can include receiving from an advertiser a request for billing based on a first measure of services, determining from quality data related to the advertiser whether the first measure of services can be converted with sufficient confidence to a second measure of services, providing services according to the first measure of services, monitoring stability data indicative of the stability of the relationship between the first measure of services and the second measure of services, and automatically switching from one to another mode of determining a price to be charged the customer for services provided.

Automatically switching between pricing models for services

Techniques are provided for selecting among the advertisements that are competing for a slot based, at least in part, on an 'schedule sequence' that is established for the advertisements. The schedule sequence may, for example, reflect the relative times at which a content provider incurred the delivery obligations associated with the advertisements. For the purpose of establishing the sequence, the date on which an advertisement order is placed may be considered to be the date on which the corresponding delivery obligations are incurred. After the sequence has been established, the position of competing advertisements within the schedule sequence is used as one of the factors for determining which competing ad to place in a slot, where ads nearer the beginning of the sequence (ads with earlier-incurred delivery obligations) are favored over ads that are nearer the end of the sequence (ads with later-incurred delivery obligations).

Selecting among advertisements competing for a slot associated with electronic content delivered over a network

Competitive content item serving is provided. Competitive content item serving can include the ability to receive a request for a content item and to compare an expected return for a first network content item to an expected return for a second network content item. Based upon the comparison, it can be determined whether to provide the first network content item to the publisher.

Competitive advertising server

Techniques are provided for selecting among the advertisements that are competing for a slot based, at least in part, on the potential revenue amounts associated with the advertisements. Each of the potential revenue amounts may, for example, reflects a value that a provider expects to receive in exchange for the provider's performance of the delivery obligations associated with the advertisements. Other factors may also be considered in selecting among the competing advertisements, such as whether the slot has been reserved for buyers that satisfy a set of criteria.

Predicting inventory availability and prioritizing the serving of competing advertisements based on contract value

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Cupertino, CA, United States of America

Bhavesh R Mehta