Many conventional advertisements designed for display as part of a web page executed by a web browser are not suitable for display in an online video player that, though included in a web page, is executed by a multimedia platform. Such conventional advertisements are referred to herein as web page advertisements. A system display a web page advertisement in the frame of such an online video player by determining characteristics of the video player in the context of the multimedia platform and converting those characteristics into a context compatible with the web browser. The system can also include a virtual web browser that executes either on the multimedia platform on a server device that is communicatively coupled to the multimedia platform. The system can also include an ad tag translator that executes either on the multimedia platform on a server device that is communicatively coupled to the multimedia platform.
Systems and methods are disclosed for targeting of advertising content for a consumer product, by obtaining consumer demographic data, the consumer demographic data including a plurality of demographic attributes for each person; identifying a plurality of media slots; and obtaining program information for a respective identified program aired in each media slot among the plurality of media slots, the program information including viewing data of a plurality of viewing persons viewing the program and each viewing person being among the plurality of persons. The methods also include enriching the viewing data with the consumer demographic data; identifying a plurality of advertiser industries; enriching the product purchaser data with the consumer demographic data; calculating a relevance of each advertiser industry among the plurality of advertiser industries for each identified program based on demographic attributes of the product purchasers in each advertiser industry and demographic attributes of the viewing persons.
H04N 21/466 - Procédé d'apprentissage pour la gestion intelligente, p. ex. apprentissage des préférences d'utilisateurs pour recommander des films
H04N 21/258 - Gestion de données liées aux clients ou aux utilisateurs finaux, p. ex. gestion des capacités des clients, préférences ou données démographiques des utilisateurs, traitement des multiples préférences des utilisateurs finaux pour générer des données collaboratives
H04N 21/2547 - Facturation de tiers, p. ex. facturation d'un publicitaire
G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
H04N 21/442 - Surveillance de procédés ou de ressources, p. ex. détection de la défaillance d'un dispositif d'enregistrement, surveillance de la bande passante sur la voie descendante, du nombre de visualisations d'un film, de l'espace de stockage disponible dans le disque dur interne
G06Q 30/0242 - Détermination de l’efficacité des publicités
H04N 21/658 - Transmission du client vers le serveur
H04N 21/24 - Surveillance de procédés ou de ressources, p. ex. surveillance de la charge du serveur, de la bande passante disponible ou des requêtes effectuées sur la voie montante
H04N 21/25 - Opérations de gestion réalisées par le serveur pour faciliter la distribution de contenu ou administrer des données liées aux utilisateurs finaux ou aux dispositifs clients, p. ex. authentification des utilisateurs finaux ou des dispositifs clients ou apprentissage des préférences des utilisateurs pour recommander des films
H04N 21/2668 - Création d'un canal pour un groupe dédié d'utilisateurs finaux, p. ex. en insérant des publicités ciblées dans un flux vidéo en fonction des profils des utilisateurs finaux
3.
System and method for attributing multi-channel conversion events and subsequent activity to multi-channel media sources
This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.
Systems and methods are disclosed that measure web activity bursts after ad broadcasts that may be sent to multiple persons. One system uses a cookie-less / cookie-optional, anonymous / personal-identification-not-required, method for web-based conversion tracking that will work on broadcast media systems such as television, and could also be applied to measuring spikes from email, radio, and other forms of advertising where an episodic ad event is broadcast to multiple parties, and where responses occur in a batch after the broadcast.
G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
H04N 21/24 - Surveillance de procédés ou de ressources, p. ex. surveillance de la charge du serveur, de la bande passante disponible ou des requêtes effectuées sur la voie montante
5.
SYSTEMS AND METHODS FOR A TELEVISION SCORING SERVICE THAT LEARNS TO REACH A TARGET AUDIENCE
Television is the largest advertising category in the United States with over 65 billion spent by advertisers per year. A variety of different targeting algorithms are compared, ranging from the traditional age-gender targeting methods employed based on Nielsen ratings, to new approaches that attempt to target high probability buyers using Set Top Box data. The performance of these different algorithms on a real television campaign is shown, and the advantages and limitations of each method are discussed. In contrast to other theoretical work, all methods presented herein are compatible with targeting the existing 115 million Television households in the United States and are implementable on current television delivery systems.
H04N 21/00 - Distribution sélective de contenu, p. ex. télévision interactive ou vidéo à la demande [VOD]
H04N 21/24 - Surveillance de procédés ou de ressources, p. ex. surveillance de la charge du serveur, de la bande passante disponible ou des requêtes effectuées sur la voie montante
H04N 21/258 - Gestion de données liées aux clients ou aux utilisateurs finaux, p. ex. gestion des capacités des clients, préférences ou données démographiques des utilisateurs, traitement des multiples préférences des utilisateurs finaux pour générer des données collaboratives
H04N 21/84 - Génération ou traitement de données de description, p. ex. descripteurs de contenu
H04N 21/2668 - Création d'un canal pour un groupe dédié d'utilisateurs finaux, p. ex. en insérant des publicités ciblées dans un flux vidéo en fonction des profils des utilisateurs finaux
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