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Big data congres 2014 benavent

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Big data congres 2014 benavent

  1. 1. Big data, des enjeux pour le marketing Christophe Benavent Professeur à Université Paris Ouest - @benavent Congrès Big Data 2014
  2. 2. 1850 : Navier-stokes WAVEWATCH III™ (Tolman 1997, 1999a, 2009) Based on of the model WAVEWATCH, as developed at Delft University of Technology (Tolman 1989, 1991a)
  3. 3. Le processus des données
  4. 4. La révolution des capteurs  Opinions et attitudes :  Le risque de la collecte sauvage  Comportements d'achat : au-delà de la caisse  Ce qu'on a pas encore pleinement exploité  Avis et Commentaires  Les défis de l'analyse du sentiment et du TAL  Détecter les intentions  Le big data c'est aussi le simple data
  5. 5. (suite)  Dynamique de la géolocalisation  Macro (granularité) et micro (Ibeacon)  Tracer le corps en mouvement  Vers le coaching digital (haptic)  Températures, pulsation et humeurs  La santé et les émotions  Les enjeux de la reconnaissance faciale  La santé et les émotions
  6. 6. Le problème de la qualité  Le problème clé des biais de sélection. – L'exemple des avis de consommateurs  Le mensonge et la dissimulation – Les réseaux sociaux  Censure, troncage et interruption – Le problème des séries chronologiques – Le traitement des cohortes => Les données brutes ça n'existe pas !
  7. 7. Des sources multiples de données  Fusion de données : – Mettre sur un même plan des données de niveaux d'analyse différents (ie CSP Iris et comportements désagrégés)  Mashup : – Associer des données de sources différentes  Open data – La logique de la restitution et des tiers => vers une architecture des données
  8. 8. 4 modèles d'utilisation des data  Le modèle de l'automatisation de la micro- décision (ie : RTB, prix)  Le nouvel enjeu de l'IA et du ML  Le modèle de la capacitation (empowerment) (ie : burberry 's)  Visualisation et Intelligence.  Le modèle des data-based services  Prescription et coaching  Le modèle des études  Modèles et sense-making : le rôle de la
  9. 9. Conclusion  Il n'y a pas de données brutes seulement des données construites – L'importance du Sense-Making et des sciences sociales  L'art de distribuer l'information dans l'organisation est la clé du succès – Organizational learning  Le big problème : un contrat de confiance et de legitimité. – Privacy paradox  L'imagination n'est pas encore au pouvoir

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