Advertising increasingly is driven by data-intensive machine learning systems. But thinking of machine learning as a black box is a mistake. The best data science starts with understanding the phenomenon being modeled. What is the relationship between the data consumers leave behind and the marketing decisions we would like to make? What do we know about human behavior that might give us an advantage? Do new data reveal new insights?
ADS*CON 2014: Embrace the Noise
After a successful inaugural event in 2013, ADS*CON returned with a new theme and new speakers to explore the impact of the data science revolution on advertising and society. ADS*CON*14 is a half-day symposium dedicated to exploring how we find meaningful signals in massive and often noisy data sets. It explored the impact of bigger and more varied data on building models and understanding markets.
Underwritten by Dstillery and the NYU Stern Center for Business Analytics, the forum featured preeminent advertising, academic and data science professionals in a fast-paced format of exploration and debate. The event helped attendees understand the vast potential of embracing the noise. The agenda was designed for CMOs, media agency executives, strategists and data scientists, as well as anyone interested in exploring the frontiers of how advertising can capitalize on advances in technology and data science.
Humans are Noisy
Welcome to the Machine
As a society, we are getting smarter about using data. As people, we tend to distance ourselves from the process of making decisions. Increasingly, the cookie crumbs and fingerprints we analyze are the results of machines talking to machines. From policing viral fraud networks to hiring for high frequency securities trading, this session explores the consequences of letting machines do our bidding.
Think you can’t teach an old dog new tricks? Think again. Despite the obvious disparities between start-ups and established companies, and between financial and technology sectors, there are some common themes in using smart data to disrupt industries.
The Data of People-Moving and Moving People
It used to be that the most granular consumer data was credit card transactions recording shopping choices. Today, we leave an extensive digital footprint with our devices, our digital media, our social networks and more. But what about our physical movements? There’s a whole new world of people data based on services that combine the physical and the digital. We take a look at public-private efforts to use data to improve transportation and urban life.
David Austin Professor Of Management, MIT. Chief Scientist, Humin.
Chief Product Officer
Scientist In Residence
VP, Data Science
Director, Center For Business Analytics
Assistant Professor In Operations And Information Management
University Of Pennsylvania
Chief Data Scientist
Director Of Research
Chief Data Scientist, VP Analytics
MassMutual Financial Group
Dstillery Co-Founder And Professor At NYU Stern
Director, Global Geocoding & Location-Based Services
CEO At WhiteOps, Director At Singularity & Co.
Director, Statistics Research Department
Director, Digital Insights And Marketing Effectiveness
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