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Faculty members Ed Malthouse and Judy Franks win award at big data conference

“Best presentation” award recognizes their research on TV advertising using big data

February 5, 2018 | By Jane Flis (IMC15) and Yunqi Zhang (IMC17)
A man and woman stand at the front of a room and speak to an audience sitting down
Medill IMC Professor Ed Malthouse (left) and Lecturer Judy Franks present at the ESOMAR conference

Medill Integrated Marketing Communications (IMC) Professor Ed Malthouse and Lecturer Judy Franks have won an award for their presentation of research on big data and “addressable” TV advertising—the ability to send a specific TV commercial to a specific customer.

ESOMAR, a nonprofit organization that promotes the value of market, opinion and social research and data analytics, presented Malthouse and Franks with the Big Data World Best Presentation Award following their presentation during the ESOMAR Big Data World 2017 conference on Nov. 29 in New York City.

Demographics don’t tell the whole story

Malthouse and Franks’ research found that demographics alone aren’t the best predictor of a customer’s purchase behavior.

It used to be that once a marketer invested in advertising, the marketer’s message was placed adjacent to the purchased content and everyone in the audience received the same message.

Advancements in programmatic digital media planning and buying changed all this. Now, marketers no longer have to buy the total audience that is associated with a particular piece of digital content. In programmatic digital display, marketers can buy ad space to reach specific customers only based on “cookies” that indicate which websites that customer has visited.

The ability to also reach specific customers through TV advertising is on the horizon. Marketers will be able to target advertising messages down to the individual household level. As technology advances, marketers are left with an important question: Which data are most important for making informed household targeting decisions on television?

In the past, we had to use demographics. Now, we have all kinds of big data.

Voting as an example

The research team looked at voting behavior in the recent Democratic and Republican presidential primaries in Texas. They wanted to know whether more detailed household demographic data would help predict Red versus Blue voting behavior, where voting for a party can be seen as purchasing its product. 

Using demographic data in machine learning models, they could predict party affiliation better than random guessing. This outcome suggests that demographics do indeed matter.

Next, the researchers wanted to know if demographics alone were enough, or if what you view is as important as who you are in determining your voting behavior. After measuring viewing behavior, their ability to predict voting outcomes increased. Sure enough, Red-voting households have many unique viewing preferences in comparison to Blue-voting households.

For example, Blue tastes tended to prefer MSNBC/CNN, "Keeping Up With the Kardashians," "Family Guy," "Walking Dead," "Undercover Boss" and "Jeopardy!" On the other hand, Red tastes preferred Fox, "Duck Dynasty," "The Waltons," "Ancient Aliens," "Shark Tank" and "Wheel of Fortune."

These findings suggest that a combination of rich demographics and rich viewing data are the perfect combination for success in addressable TV advertising.

“If you just looked at who I am based on demographics, you’d only see that I am a 54-year-old female who lives in Chicago,” said Franks. “But I also love to watch baseball, "Nashville" and "This is Us." These aren’t the type of shows you would predict I would watch based on my demographics alone. The specific content you watch should matter to advertisers in this new media ecosystem.”

Left-brain, right-brain thinking

This research was a perfect meeting of the minds, and a clear demonstration of the value of the left-brain and right-brain approach of IMC.

Malthouse has a PhD in statistics from Northwestern and is an expert at developing statistical models and applying them to large data sets of consumer information to help managers make marketing decisions. 

Franks is an advertising industry expert and had a 23-year career in Chicago’s leading ad agencies, where she rose to the executive ranks across both media and creative strategy. Her interests lie in bringing knowledge from academia to light in ways that can have real and immediate impact in the marketplace. 

“Our brains are different, and because of that, we landed in really cool places,” Franks said. “Winning this award was so gratifying because it was a team sport. 

 


The research was conducted through Medill IMC’s Spiegel Research Center by Malthouse and Franks as well as Ewa Maslowska, assistant professor at University of Amsterdam.

An article about this research was published in Medill’s 2018 edition of the Journal of Integrated Marketing Communications. The article, co-authored by Malthouse and Franks, was edited by Medill IMC student Yunqi Zhang (IMC17).

Medill IMC master’s students can get involved with SRC by being Spiegel Research Fellows or serving on the Impact Marketing Team.

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