Patent application number | Description | Published |
20110029666 | Method and Apparatus for Passively Monitoring Online Video Viewing and Viewer Behavior - Various user behaviors are passively monitored and recorded when a user/viewer interacts with a network video player, e.g. a web video player, while watching an online video clip. For one embodiment, a data collection agent (DCA) is loaded to the player and/or to a web page that displays the video clip. The DCA passively collects detailed viewing and behavior information without requiring any specific input or actions on the part of the user. Indications of user preferences are inferred by user actions leading up to viewing the video, while viewing the video, and just after and still related to viewing the video. The DCA periodically sends this information to a central server where it is stored in a central database and where it is used to determine preference similarities among different users. Recorded user preference information may also be used to rate a video itself. | 02-03-2011 |
20110225608 | Video Viewer Targeting based on Preference Similarity - Presentation of a video clip is made to persons having a high probability of viewing the clip. A database containing viewers of previously offered video clips is analyzed to determine similarities of preferences among viewers. When a new video clip has been watched by one or more viewers in the database, those viewers who have watched the new clip with positive results are compared with others in the database who have not yet seen it. Prospective viewers with similar preferences are identified as high likelihood candidates to watch the new clip when presented. Bids to offer the clip are based on the degree of likelihood. For one embodiment, a data collection agent (DCA) is loaded to a player and/or to a web page to collect viewing and behavior information to determine viewer preferences. Viewer behavior may be monitored passively by different disclosed methods. | 09-15-2011 |
20130339523 | METHOD AND APPARATUS FOR PASSIVELY MONITORING ONLINE VIDEO VIEWING AND VIEWER BEHAVIOR - Various user behaviors are passively monitored and recorded when a user/viewer interacts with a network video player, e.g. a web video player, while watching an online video clip. For one embodiment, a data collection agent (DCA) is loaded to the player and/or to a web page that displays the video clip. The DCA passively collects detailed viewing and behavior information without requiring any specific input or actions on the part of the user. Indications of user preferences are inferred by user actions leading up to viewing the video, while viewing the video, and just after and still related to viewing the video. The DCA periodically sends this information to a central server where it is stored in a central database and where it is used to determine preference similarities among different users. Recorded user preference information may also be used to rate a video itself. | 12-19-2013 |
20140108159 | SIMULATOR FOR A REAL-TIME BIDDING SYSTEM - A multistage online auction for electronic advertising is described including simulation. A first stage auction occurs internally within a demand-side platform where multiple advertiser clients compete to determine whose advertisement is submitted to at least one external auction site. Within the internal auction, an advertiser client optionally simulates their participation. All bidders enter a bid and campaign targeting parameters. A simulating bidder's campaign is processed in real time just as those of real bidders. Ad placement opportunities received from an external auction site are filtered for each campaign producing a list of targetable impressions. For each targetable impression, the client placing the highest real bid has their ad and bid submitted to the second stage external auction. A simulating bidder receives a report on targetable impressions for their campaign. A targetable impression for a simulated bid that is higher than any real bid is reported as a winnable impression. | 04-17-2014 |
20140278749 | METHOD AND APPARATUS FOR DETERMINING WEBSITE POLARIZATION AND FOR CLASSIFYING POLARIZED VIEWERS ACCORDING TO VIEWER BEHAVIOR WITH RESPECT TO POLARIZED WEBSITES - Websites and viewers are characterized for online advertising media campaigns, enabling online bidding capabilities for media campaigns, including pricing based on delivered Gross Rating Points (GRPs) instead of delivered impressions. GRPs for a campaign are estimated based on characterizing polarized Websites and then characterizing polarized viewers. A truth set of viewers having known characteristics is established and then compared with historic and current media viewing activity to determine a degree of polarity for different Media Properties (MPs), such as Websites offering ads, with respect to viewer characteristics such as gender and age bias. A broader base of polarized viewers is then characterized for age and gender bias, and their propensity to visit a polarized MP is rated. Based on observed and calculated parameters, bidding functionalities are enabled, including predicting a GRP total and pricing GRPs to a client and/or advertiser for an online ad campaign. | 09-18-2014 |
20140278912 | Systems and Methods for Predicting and Pricing of Gross Rating Point Scores by Modeling Viewer Data - Systems and methods are disclosed for characterizing websites and viewers, for predicting GRPs (Gross Rating Points) for online advertising media campaigns, and for pricing media campaigns according to GRPs delivered as opposed to impressions delivered. To predict GRPs for a campaign, systems and methods are disclosed for first characterizing polarized websites and then characterizing polarized viewers. To accomplish this, a truth set of viewers with known characteristics is first established and then compared with historic and current media viewing activity to determine a degree of polarity for different Media Properties (MPs)—typically websites offering ads—with respect to gender and age bias. A broader base of polarized viewers is then characterized for age and gender bias, and their propensity to visit a polarized MP is rated. Based on observed and calculated parameters, a GRP total is then predicted and priced to a client/advertiser for an online ad campaign. | 09-18-2014 |
20140278937 | Systems and Methods for Predicting and Pricing of Gross Rating Point Scores by Modeling Viewer Data - Systems and methods are disclosed for characterizing websites and viewers, for predicting GRPs (Gross Rating Points) for online advertising media campaigns, and for pricing media campaigns according to GRPs delivered as opposed to impressions delivered. To predict GRPs for a campaign, systems and methods are disclosed for first characterizing polarized websites and then characterizing polarized viewers. To accomplish this, a truth set of viewers with known characteristics is first established and then compared with historic and current media viewing activity to determine a degree of polarity for different Media Properties (MPs)—typically websites offering ads—with respect to gender and age bias. A broader base of polarized viewers is then characterized for age and gender bias, and their propensity to visit a polarized MP is rated. Based on observed and calculated parameters, a GRP total is then predicted and priced to a client/advertiser for an online ad campaign. | 09-18-2014 |
20140278938 | Systems and Methods for Predicting and Pricing of Gross Rating Point Scores by Modeling Viewer Data - Systems and methods are disclosed for characterizing websites and viewers, for predicting GRPs (Gross Rating Points) for online advertising media campaigns, and for pricing media campaigns according to GRPs delivered as opposed to impressions delivered. To predict GRPs for a campaign, systems and methods are disclosed for first characterizing polarized websites and then characterizing polarized viewers. To accomplish this, a truth set of viewers with known characteristics is first established and then compared with historic and current media viewing activity to determine a degree of polarity for different Media Properties (MPs)—typically websites offering ads—with respect to gender and age bias. A broader base of polarized viewers is then characterized for age and gender bias, and their propensity to visit a polarized MP is rated. Based on observed and calculated parameters, a GRP total is then predicted and priced to a client/advertiser for an online ad campaign. | 09-18-2014 |
20140289017 | Methods for Viewer Modeling and Bidding in an Online Advertising Campaign - Systems and methods are disclosed for employing supervised machine learning methods with activities and attributes of viewers with truth as input, to produce models that are utilized in determining probabilities that an unknown viewer belongs to one or more demographic segment categories. Using these models for processing viewer behavior, over a period of time a database of known categorized viewers is established, each categorized viewer having a probability of belonging to one or more segment categories. These probabilities are then used in bidding for online advertisements in response to impression opportunities offered in online media auctions. The probabilities are also used in predicting on-target impressions and GRPs (Gross Rating Points) in advance of online advertising media campaigns, and pricing those campaigns to advertiser/clients. Strategies are also disclosed for fulfilling a campaign when an available inventory of known categorized viewers is not adequate to fulfill a campaign in a required runtime. | 09-25-2014 |