|Individuals and organizations interact through many channels, on multiple screens and devices, across a myriad of touchpoints and over time. Given the ubiquity of data, there is a new opportunity for firms to more fully understand the effect and value of their marketing actions. Big data, experimentation, and new models offer new insight into the causal levers and influences in this complex, extended world.|
Causality, Optimality, and Marketing ModelingFeb 09, 2017 Peter E. Rossi, University of California, Los Angeles
The role of causal inference is to establish the true effect sizes for various marketing actions. As such, causal inference relies heavily on counterfactual reasoning. Peter Rossi will review the basics of causal inference and provide examples of valid reasoning and challenges for existing practices.
TV Ads and Search Spikes: Toward a Deeper UnderstandingFeb 09, 2017 Kenneth C. Wilbur, University of California, San Diego
Mobile devices and media multi-tasking have become so common that Google search spikes can now be detected in response to "mundane" TV ads. The question is, does search reliably predict intent?
Advertising Spending in the Digital AgeFeb 09, 2017 Shuba Srinivasan, Boston University
Much has been learned about the impact of advertising on business performance. But do these lessons still hold in the digital age?
Two Views on the Future of Marketing AnalyticsFeb 09, 2017 Koen Pauwels, Özyeğin University
What does the future hold? Deep learning, self-service analytics, confirmation bias, fast hypothesis testing, augmented reality, IoT?
The New Market Research Landscape in Media and EntertainmentFeb 09, 2017 Matt Kautz, Vice President of Business Intelligence, Analytics and Research, Machinima
How can marketers in the media and entertainment industry use these data sets to address their strategic questions? Matt Kautz will present a framework and offer a deep-dive into some case studies on creative optimization, forecasting, and media targeting.
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