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In-car system to combat viruses, pollution wins GfK NextGen Data Science Competition

Press Releases

In-car system to combat viruses, pollution wins GfK NextGen Data Science Competition



Experts from Hyundai, Kia, Team One acted as judges for 10-day hackathon focused on smart car technology

Tapping into today’s elevated concerns about viruses like COVID-19 – as well as other airborne diseases and pollutants – a team of undergraduates from Point Park University has won the second annual GfK NextGen Data Science Hackathon Competition.

GfK challenged students to develop strategic recommendations for a new “smart car” product that would leverage digital technology. The teams worked with a variety of GfK data sets to understand unmet consumer needs, articulate new offerings, and outline marketing plans.

The Point Park students focused on a theoretical product called SAPS (Surface and Air Purification System), which would use HEPA air filtration and ultra-violet light to help eliminate allergies, diseases, and impurities inside of cars.

To develop their ideas and strategies, NextGen teams were provided with access to data from unique GfK assets, including MRI’s Survey of the American Consumer®, GfK Consumer Life, GfK AutoMobilty™, and a new AutoMobililty-linked behavioral dataset. 

On Thursday, four finalist teams were given 5 minutes each to present their proposals to a panel of judges – GfK data science experts, as well as three GfK clients from major auto manufacturers:

  • Steve Kosowski – Manager, Long-Range Planning and Strategy at Kia Motors America
  • Vijay Rao — Senior Group Manager, Digital Business and Connected Ops at Hyundai Motor America
  • Ganesh Relekar – Director, Strategic Analytics at Team One

Participants were assessed on a variety of criteria, focusing both on data skills and business intelligence. The winning Point Park University team – which takes home a $5,000 cash award – delivered a strong combination of specific recommendations, clear data support, and presentation skills. The Point Park team are

  • Ibrokhim Mirzakhonov – Information Technology (Senior)
  • Sabrina Tatalias – Information Technology (Junior)
  • Emily VanderMey – Information Technology & Marketing (Senior)

The Point Park students were mentored by Dr. Dorene Ciletti, Associate Professor and Program Director for Marketing and Sales, and Dr. Mark Voortman, Associate Professor and Program Director for Information Technology.

The runner-up project came from a team of students at California State Polytechnic University (Pomona), who proposed a car safety product that would be supported by Google data streams. A second team from the same university also reached the finals, as did a group of students from last year’s winning school, City University of New York’s College of Staten Island.

“We were thrilled to see the students this year responding to the top concerns that GfK is tracking among consumers – COVID-19 in particular, but also personal safety and data security,” said Rolfe Swinton, GfK’s Director of Data Assets for North America. “Their command of the data and ability to present cogent strategic plans in just 5 minutes bodes well for the future of data science – and for the smarter business decisions GfK is helping clients achieve. We are pleased to be giving these student teams a hands-on experience with the types of data that are driving so many companies and innovations today.”    

Two years ago, GfK North America reimagined its annual NextGen Competition – which previously focused on traditional research methods – as a 10-day hackathon, in which students mined raw data sets for relevant insights and then converted them into business guidance. The change reflects a radical transformation in market research, in which data integration and predictive analysis now play dramatically larger roles.

In previous years, teams from Aurora University, Chatham University, Loyola University (Chicago), Purdue University (Calumet), and Roosevelt University won top GfK NextGen Competition honors, in contests focused on traditional market research methods – but still employing data science and analysis.