Abstract: The present invention provides techniques associated with online advertisement brand engagement value, which can be of critical importance to brand advertisers. Techniques are also included involving use of brand engagement value across various online and offline advertising media and venues. Techniques are provided in which experiments are conducted, such as eyeball-tracking experiments, which include measurements to determine brand engagement value of particular online advertisement impressions. Information from the experiments is utilized in making determinations of brand engagement value, or anticipated brand engagement value, of online advertisement impressions for which brand engagement value has not been measured.

Abstract: The present invention provides methods and systems for use in online advertising campaign management, including bid management in an online advertising auction. Techniques are provided in which a benchmark set of previously served advertisements is identified, and associated performance information is obtained. During an online auction, when an advertisement impression opportunity becomes available, information obtained using a machine learning technique may be utilized in forecasting an advertiser value-based metric associated with the opportunity, using the benchmark set of advertisements and the associated performance. The forecasted advertiser value-based metric can be used in determining bidding and pricing associated with the opportunity.

Abstract: A method and system are provided for building data objects for online display advertising. In one example, the method includes providing two or more forms configured for receiving data objects for an ad campaign, wherein the two or more forms sufficiently compartmentalize the ad campaign in order to facilitate entry of the data objects, providing a navigation interface configured for facilitating navigation among the two or more forms, receiving the data objects into the two or more forms, and receiving at least one request into the navigation interface.

Abstract: Metrics for evaluating content layout performance are provided which enable the dynamic generation of content layouts optimized for particular target audiences, types of content, and/or delivery channels.