Data Scientists Gilad Barash, Reka Daniel-Weiner and Peter Lenz explore how supplementing traditional market research with AI turns 160 billion data points per day of observed consumer behavior into meaningful, actionable intelligence. Watch the recording from our Greenbook Webinar.
In this webinar, you will learn:
- How to scale your market research capabilities by going beyond traditional methods based on self-reported behavioral data.
- How to capture observed behavioral data from actions that consumers take in both the digital and physical world and how to ensure the data is high quality, fraud-free, and privacy friendly.
- How to combine observed and self-reported data to create a more holistic view of the consumer journey.
Gilad Barash, Director of Analytics, Dstillery
Gilad Barash has been driving innovative work on the analytics team at Dstillery for over three years. Previously, he held various roles at HP including creating decision support for Enterprise IT systems, and held roles in Research and Engineering at HP Labs Israel. As a research assistant at Tufts, he worked to improve personalized healthcare. He is named on five patents, and is an author of published research papers across four scientific journals. Gilad also spent five years in the Israeli Defense Force in both active military and operational roles. He holds a B.S. and and M.S. in Computer Science from San Diego State University.
Reka Daniel-Weiner is a Data Scientist at Dstillery in New York, where she uses behavioral and location data to inform and optimize machine learning systems which find prospective customers for brands and target them with display advertisements online. In addition, she is involved in developing digital intelligence solutions to help brands understand who their current and prospective customers are, and how to optimally reach them across different channels. In her recent work she has focused on determining the causal effect of online display advertisements on in-store purchase of consumer packaged goods. Prior to joining Dstillery, she was Postdoctoral Research Associate at the Princeton Neuroscience Institute. There she developed reinforcement learning models to explore human decision making in multidimensional environments. She received a PhD in cognitive psychology in 2012 from the Otto-von-Guericke University in Magdeburg, Germany.
Peter Lenz is a geographer and data scientist with Dstillery, a data insights company that builds behavioral profiles from billions of observations of human behavior every day using AI. Specializing in geographic big data and data storytelling, Peter can dive anywhere into the data pipeline from writing code, training models, to discovering insights in the data. He built up skill set working in the urban planning world, first at a consulting firm and later with an agency of the Department of the Interior. A native of New York City, today he and his family live in the Hudson Valley.