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Home | Events Archive | Using text for Business Insights

Using text for Business Insights

  • Series
    BDS Marketing Seminars
  • Speakers
    Oded Netzer (Columbia University, United States)
  • Field
  • Location
  • Date and time

    August 31, 2021
    15:00 - 15:30

This seminar is part of the joint Marketing Seminars Series at Business Data Science (VU, UvA, and ESE) with a fantastic line-up of speakers that will present their research online in the Marketing Science elective course and seminar series. View all upcoming seminars in our events calendar. Please send an email to seminar@businessdatascience.nl if you are interested to participate in this seminar (series) and are not yet on the mailing list.

Based on some estimates 80-95% of all data available to businesses are unstructured including text, image, video and audio data. Specifically, textual data and words are ubiquitous in almost every marketplace interaction from user generated content to company reports, to service interactions and marketing communications. These interactions create a wealth of textual data. This data source is on the one hand exciting and rich, but on the other hand, by it its unstructured nature, difficult to decode and derive insights from. How can business leaders best use such data? This talk will discuss several papers that explore the use of textual data for business decision making.

15:00-15:30: Presentation - Oded Netzer (Columbia University, United States) (online seminar)
15:30-16:30: Discussion with the speaker

There will be 30 minutes of presentation, and roughly an hour of post-discussion with the research master and PhD students. Should you want to be present for this post-discussion (a “look behind the scenes”), feel free to let us know at seminar@businessdatascience.nl

Professor Netzer's expertise centers on one of the major business challenges of the data-rich environment: developing quantitative methods that leverage data to gain a deeper understanding of customer behavior and guide firms' decisions. He focuses primarily on building statistical and econometric models to measure consumer preferences and understand how customer choices change over time, and across contexts. Most notably, he has developed a framework for managing firms' customer bases through dynamic segmentation. More recently, his research focuses on leveraging text-mining techniques for business applications.

Professor Netzer published numerous papers in the leading scholarly journals. His research was nominated for and won multiple awards and serves on the editorial board of several leading journals including: Marketing Science, Management Science, Journal of Marketing Research, Journal of Marketing, Quantitative Marketing and Economic, and International Journal of Research in Marketing.

Professor Netzer frequently consult to Fortune 500 companies and entrepreneurial organization on strategy, data-driven decision making, marketing research and extracting useful information from rich and thin data.