SMITH BRAIN TRUST — There’s no question that internet advertising is increasingly vital for business survival. The question is: Where do you start? And how can you be sure that your advertising dollars are reaching the right audience?
In search of those answers, companies more and more are turning to ad agencies and demand-side platforms (DSPs). It’s a good first step. However, most extant DSP algorithms remain rule-based and strictly proprietary. “So it’s hard to tell how your dollars are being spent, and who’s actually viewing your ads,” says Courtney Paulson, assistant professor at the University of Maryland’s Robert H. Smith School of Business.
Working with two co-authors, Paulson developed a non-proprietary algorithm that specifically considers viewership correlations across websites. That way, campaign managers can focus their ad dollars in as few places as possible to reach the desired audience.
For example, if 95 percent of people who read Businessweek.com also read Reuters.com, and vice versa, as indicated by Internet viewing datasets, then there’s little point to advertising in both places. Dollars might be more wisely spent elsewhere, to reach another segment of your desired audience.
The co-authors’ method takes that into account, and also offers a budget-setting tool with guidelines on bidding for ad space, Paulson says. And it addresses a range of other practical considerations, from targeted consumer demographics, frequency of ad exposure, mandatory media coverage to matched content websites, and more.
“You have to make decisions so quickly with internet advertising,” says Paulson. “And having to rely on split-second bidding sometimes means sort of just making your best guess, because a lot of the algorithms that people use aren’t particularly advanced.”
Read more: “Efficient Large-Scale Internet Media Optimization,” by Courtney Paulson, and University of Southern California co-authors Lan Luo and Gareth M. James.
Courtney Paulson is an assistant professor of Decision, Operations and Information Technologies at the University of Maryland’s Robert H. Smith School of Business. She received her B.S. in Statistics from the University of Central Florida in 2011 and her Ph.D. in Business Administration (Statistics) from the University of Southern California in 2016.
Research interests: Algorithm development, constrained optimization models, and systems architecture. Her work focuses on interdisciplinary data analytics applications, which has led to projects with researchers across domains such as marketing, operations, engineering, and systems analysis.
Selected accomplishments: Paulson’s work has been recognized with awards from statistical organizations, including the American Statistical Association, and organizations outside the statistics discipline, including the INFORMS Society of Marketing Science, which recently honored her with the 2015-2016 ISMS Doctoral Dissertation Award. She’s also a one-time champion of the TV game show “Jeopardy!”
About this series: The Smith School faculty is celebrating Women’s History Month 2017 in partnership with ADVANCE, an initiative to transform the University of Maryland by investing in a culture of inclusive excellence. Daily faculty spotlights support activities from the school’s Office of Diversity Initiatives, culminating with the sixth annual Women Leading Women forum on March 30, 2017.
Other fearless ideas from: Rajshree Agarwal | Ritu Agarwal | Leigh Anenson | Kathryn M. Bartol | Christine Beckman | Margrét Bjarnadóttir | M. Cecilia Bustamante | Rellie Derfler-Rozin | Waverly Ding | Wedad J. Elmaghraby | Rosellina Ferraro | Rebecca Hann | Amna Kirmani | Hanna Lee | Hui Liao | Wendy W. Moe | Courtney Paulson | Louiqa Raschid | Rebecca Ratner | Rachelle Sampson | Debra L. Shapiro | Cynthia Kay Stevens | M. Susan Taylor | Vijaya Venkataramani | Janet Wagner | Yajin Wang | Yajun Wang | Liu Yang | Jie Zhang | Lingling Zhang | PhD Candidates
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