Abstract: A system for analyzing user consumption of content on web pages or determining user engagement with content comprising a data collection script and an content-engagement-inference engine. The data collection script determines one or more content elements to be measured from a web page and collects description data associated with the one or more content elements. The description data describes information about the one or more content elements. The content-engagement-inference engine creates an inference or analytics result based on the description data. The inference or analytics result describes how the one or more content elements have been consumed by users and then provides the inference or analytics result for users to designated entities.

Abstract: A system and methods for providing data to interested entities (e.g., publisher or advertiser) on consumer behavior when viewing advertising displayed on web pages is described. In some implementations, a JavaScript tag or other code is designated with the purpose of examining and communicating the consumer behaviors of web page consumers to an external server. The JavaScript tag is equipped with a customized pixel or similar signaling software, which is invoked under certain pre-defined conditions associated by any one of the interested entities with the JavaScript Tag and known to all users (e.g. publisher or advertiser) of the JavaScript Tag.

Abstract: A system and methods for providing accurate counting of advertisement impressions is described. The system and methods include bloom filter technology or other space-efficient probabilistic data structure algorithms to efficiently determine whether any particular advertisement impression across an enormous set of possibilities has been viewed previously or not, without having to search through every instance of rendering of any particular advertisement impression. The present system and methods include arrays of multiple bloom filters and manipulate them to correct for false positives when conditions create the risk of false positives that may have occurred during data capture on a browser. In addition, the system and methods generate unique qualification identifiers for advertising served, which is evaluated by the bloom filters before a count is incremented.