Capturing Information to Fuel Growth
Social Media’s Impact on Consumer Mindset: When to Use Which Sentiment Extraction Tool?Sep 21, 2017 Raoul V. Kübler, Anatoli Colicev, and Koen Pauwels, 2017, 17-122-09
Which method should marketers use to gauge consumer feelings from user-generated content? This award-winning study compares sentiment extraction tools -- from volume metrics to dictionaries and machine learning -- to see which works best to explain customer metrics such as brand awareness, image, purchase intent, customer satisfaction, and recommendation.
Search Personalization Using Machine LearningAug 14, 2017 Hema Yoganarasimhan, 2017, 17-117-08
Applied to data from search engine Yandex, this machine learning framework improved clicks to the top position by 3.5% and reduced average error in click rank by 9.4% over baseline. For marketers, the question is, how will users trade off the use of their individual data (albeit anonymized) with the gains of a better search experience?
Virtual Reality for Shopper ResearchAug 2, 2017 Raymond R. Burke, Indiana University, 2017, 17-116-08
Today, virtual reality simulations can help marketers test new ideas and more accurately predict consumers' in-store behavior. In the near future, virtual stores may become a viable channel of distribution, combining the convenience and transparency of online shopping with the engagement of a video game.
Drivers of Metric Use in Marketing Mix Decisions: An Investigation across the G7, BRIC, and MIST CountriesJun 12, 2017 Ofer Mintz, Jan-Benedict E.M. Steenkamp, Martijn de Jong, and Imran S. Currim, 2017, 17-113-06
Analysis of over 4,000 marketing-mix decisions in 16 countries offers important insights for top execs who need to understand and drive downstream managerial metric use.
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