Big Data Lecture Series

Thursday, April 18, 2019

5:00pm - 6:30pm, Clendenin Building, room 1008 (CL 1008), Kennesaw Campus (PDF)

"Transforming Journalism with Practical Application of Data Science"

  • Luke Boutwell, Ph.D. Manager, Special Projects
  • Brendan Meany, Manager
  • Tad Zhang, Senior Data Scientist at Mather Economics

ABSTRACT: The landscape of the media industry is changing and media companies must shift to a digitally-driven business model. This presents both challenges and opportunities. At Mather Economics, we analyze user behavioral data, content production, marketing messaging, and other web data in order to help media companies adapt to an increasingly paperless world. Our approach applies practical machine learning strategies to build predictive models in the news media industry to optimize revenue and user experience. Here, we'll describe our approach and present real world applications and results of our modeling.

Photo of Luke BoutwellBIO: In his role as Manager for Special Projects, Luke Boutwell, focuses on projects that have unique analytical and conceptual challenges. He uses advanced statistical methods and economic theory to design solutions to difficult problems in a variety of settings. Luke’s clients include international media companies, environmental non-profits, agricultural consultancies, and eCommerce companies, among others. Luke also serves as an internal resource for research and development, promoting creative solutions for new clients and industries and continuing development for existing products and services. Luke holds a Doctoral degree in Agricultural Economics from Louisiana State University with concentrations in Environmental Economics and Econometrics, a Master of Science degree in Agricultural Economics from Louisiana State University, and a Bachelor of Science degree in Geography from the University of Alabama.

Photo of Brendan MeanyBIO: Brendan Meany focuses on developing and implementing strategies tailored toward revenue growth, retention initiatives, acquisition and re-acquisition for clients. He creates optimal pricing strategies which point clients to sound pricing actions and builds econometric models to inform renewal pricing, stop-save tactics, and acquisition best practices.  Additionally, Brendan builds models to estimate the value of content and has published an online article alongside a client which describes revenue generated via an introduced opt-in piece. Further, he has implemented subscriber digital conduct into his models, adding an extra layer of behavioral variability among subjects modeled. Brendan holds a Master of Science degree in Applied Economics, a Bachelor of Science degree in Ecology, and a Bachelor of Science degree in Environmental Economics, all from the University of Georgia.

Photo of Tad ZhangBIO: Tad Zhang is specialized in profiling click stream data to uncover the unique patterns that attributes to different characteristics of online users. He focuses on solving challenging data issues and creates actionable solutions. Over the course at Mather Economics, Tad has taken initiatives on building various products and data structure to support the Listener™ data science team. Tad holds dual degrees in Actuarial Science and Risk Management from Georgia State University.

    • Tuesday, April 16, 2019 - Bogdan Gadidov