Neil Hoyne

Systems, methods, and computer-readable storage media that may be used to generate a competitive metric are provided. One method includes receiving interaction data elements including identifiers and time stamps and generating a path data structure. A path data structure includes the interaction data elements sorted by identifier and time stamp. Further, the method includes sorting, parsing, and filtering the path data structure to generate a minor path data set. The method includes generating… Show more

Systems, methods, and computer-readable storage media that may be used to generate a competitive metric are provided. One method includes receiving interaction data elements including identifiers and time stamps and generating a path data structure. A path data structure includes the interaction data elements sorted by identifier and time stamp. Further, the method includes sorting, parsing, and filtering the path data structure to generate a minor path data set. The method includes generating the competitive metric by using the minor path data set to determine the number of interactions an entity has with a group of content providers and comparing that number of interactions to the number of interactions a second entity has with the same group of content providers. Show less

An advertisement targeting system manages content and advertisements on a website. The system receives a request to place measurement units on a publisher website from a publisher. The system receives a request to purchase an inventory of measurement units from an advertiser to target content or advertisements on the advertiser’s destination website. Further, the system identifies an inventory of measurement units based on an association between the publisher websites with the measurement units… Show more

An advertisement targeting system manages content and advertisements on a website. The system receives a request to place measurement units on a publisher website from a publisher. The system receives a request to purchase an inventory of measurement units from an advertiser to target content or advertisements on the advertiser’s destination website. Further, the system identifies an inventory of measurement units based on an association between the publisher websites with the measurement units and the destination website. Upon identifying the inventory of the measurement units, the system captures user behavior at the publisher websites with the inventory of the measurement units. Further, the system customizes content on the destination website for a user based on the captured user behavior. Show less

Content providers often publish content items in networked resources through online content management systems with the goal of having an end user interact with (e.g., click through) the content items and perform a converting action, such as providing information of value to the content providers and/or purchasing a product or service offered by the content providers. The quality of content item impressions and/or placements published within resources can have a substantial impact in driving… Show more

Content providers often publish content items in networked resources through online content management systems with the goal of having an end user interact with (e.g., click through) the content items and perform a converting action, such as providing information of value to the content providers and/or purchasing a product or service offered by the content providers. The quality of content item impressions and/or placements published within resources can have a substantial impact in driving incremental conversions. In some cases, the quality of the impressions may have a more substantial impact than clicks in driving conversions. Show less

Method includes receiving path data representing a plurality of paths and identifying one or more negative interactions within one or more of the paths ending in an interaction other than a conversion. Each negative interaction includes one of one or more types of interactions that decrease a likelihood of a path resulting in a conversion. The method further includes, for each of the one or more negative interactions, determining an estimated probability that the one or more paths including the… Show more

Method includes receiving path data representing a plurality of paths and identifying one or more negative interactions within one or more of the paths ending in an interaction other than a conversion. Each negative interaction includes one of one or more types of interactions that decrease a likelihood of a path resulting in a conversion. The method further includes, for each of the one or more negative interactions, determining an estimated probability that the one or more paths including the negative interaction would have resulted in a conversion if the one or more paths excluded the negative interaction. The method further includes estimating an amount of lost revenue associated with one or more of the negative interactions based on the estimated probability. Show less

Method includes determining conversion path data and determining, for each of a plurality of domains: (1) a first metric based on a first set of the conversion paths for which interactions related to the domain are earlier in the conversion paths than one or more last interactions prior to the conversion actions; (2) a second metric based on a second set of the conversion paths for which interactions related to the domain are one of the one or more last interactions prior to the conversion… Show more

Method includes determining conversion path data and determining, for each of a plurality of domains: (1) a first metric based on a first set of the conversion paths for which interactions related to the domain are earlier in the conversion paths than one or more last interactions prior to the conversion actions; (2) a second metric based on a second set of the conversion paths for which interactions related to the domain are one of the one or more last interactions prior to the conversion actions; and (3) an analysis metric based on the first metric and the second metric. The method further includes generating one or more recommendations for obtaining content placements in one or more of the domains based on the analysis metrics for the domains. Show less

Method includes receiving lead data and determining path data representing one or more paths including one or more interactions leading to submission of the lead data. The method further includes determining a cost metric representing a cost to a content provider of the one or more interactions leading to submission of the lead data, a delay metric between a first interaction of the one or more interactions and submission of the lead data, and an engagement metric relating to a level of… Show more

Method includes receiving lead data and determining path data representing one or more paths including one or more interactions leading to submission of the lead data. The method further includes determining a cost metric representing a cost to a content provider of the one or more interactions leading to submission of the lead data, a delay metric between a first interaction of the one or more interactions and submission of the lead data, and an engagement metric relating to a level of engagement of the device identifier with one or more resources associated with the content provider prior to submission of the lead data. The method further includes generating an effort score based on a combination of the cost metric, the delay metric, and the engagement metric. Show less

Method includes receiving user path data representing a plurality of user paths. The method further includes identifying a plurality of user paths ending with an abandonment event associated with a first resource. The method further includes determining a first abandonment metric indicating a first plurality of the identified user paths having a first condition of a characteristic. The method further includes determining a second abandonment metric indicating a second plurality of the… Show more

Method includes receiving user path data representing a plurality of user paths. The method further includes identifying a plurality of user paths ending with an abandonment event associated with a first resource. The method further includes determining a first abandonment metric indicating a first plurality of the identified user paths having a first condition of a characteristic. The method further includes determining a second abandonment metric indicating a second plurality of the identified user paths having a second condition of the characteristic. The method further includes determining whether the abandonment events associated with the first resource are at least partially related to the characteristic based on a comparison of the first abandonment metric and the second abandonment metric. Show less

Method includes receiving user path data representing a plurality of user paths, each including one or more sales interactions in which a user was presented with an offer to purchase an item at an offer price. One or more user paths include conversion events in which the user purchases the item. The method further includes receiving competitive price data indicating one or more prices at which the item was offered for sale by one or more third party entities and determining a… Show more

Method includes receiving user path data representing a plurality of user paths, each including one or more sales interactions in which a user was presented with an offer to purchase an item at an offer price. One or more user paths include conversion events in which the user purchases the item. The method further includes receiving competitive price data indicating one or more prices at which the item was offered for sale by one or more third party entities and determining a price-competitiveness metric for at least one of the sales interactions based on a comparison of the offer price with the competitive price data. The method further includes providing data based on the price-competitiveness metric to the content provider. Show less

Method includes determining conversion path data for a content provider. The method further includes determining a plurality of organic search keywords within the conversion path data. The method further includes analyzing the plurality of organic search keywords within the conversion path data to generate an analysis metric for each of the plurality of organic search keywords. The method further includes selecting one or more of the plurality of organic search keywords based on the analysis… Show more

Method includes determining conversion path data for a content provider. The method further includes determining a plurality of organic search keywords within the conversion path data. The method further includes analyzing the plurality of organic search keywords within the conversion path data to generate an analysis metric for each of the plurality of organic search keywords. The method further includes selecting one or more of the plurality of organic search keywords based on the analysis metrics for the organic search keywords, and generating one or more recommendations for new content to be published by the content provider based on the selected one or more organic search keywords. Show less

Method includes determining conversion path data for a content provider. The method further includes determining a plurality of organic search keywords within the conversion path data. The method further includes analyzing the plurality of organic search keywords within the conversion path data to generate an analysis metric for each of the plurality of organic search keywords. The method further includes generating one or more recommendations for organic search keywords to add to the set of… Show more

Method includes determining conversion path data for a content provider. The method further includes determining a plurality of organic search keywords within the conversion path data. The method further includes analyzing the plurality of organic search keywords within the conversion path data to generate an analysis metric for each of the plurality of organic search keywords. The method further includes generating one or more recommendations for organic search keywords to add to the set of paid keywords based on the analysis metrics for the plurality of search keywords. Show less

Method includes calculating a cumulative user cost based on previous interactions of a user with one or more content items of a content campaign. The method further includes determining an expected revenue contribution resulting from a conversion. The method further includes determining whether to cause a content management system serving content items to limit serving of content items of the content campaign to the user based on the comparison of the cumulative user cost to the expected… Show more

Method includes calculating a cumulative user cost based on previous interactions of a user with one or more content items of a content campaign. The method further includes determining an expected revenue contribution resulting from a conversion. The method further includes determining whether to cause a content management system serving content items to limit serving of content items of the content campaign to the user based on the comparison of the cumulative user cost to the expected revenue contribution. Show less