Turning coursework into holistic problem-solving for modern marketing issues
Embracing the changing whims of a dynamic consumer base is a cornerstone of marketing. Yet it’s often debatable when and how brands should initiate change alongside such an erratically evolving culture.
“You can’t really talk about the problems that managers were facing five years ago, or even two years ago, because marketing is such a dynamic discipline,” said Vamsi Kanuri, who created and teaches the Marketing Decision Models course for undergraduate and MBA students at the University of Notre Dame’s Mendoza College of Business. “It’s almost impossible for me to keep the current content static.”
Luckily, Kanuri, an associate professor of marketing, is able to regularly draw new content and decision models into his class via his prolific research. Using econometric, optimization and machine-learning techniques, he evaluates the performance and consumer welfare implications of marketing strategies within the domains of social media, services and multichannel marketing. Each time he publishes a paper, Kanuri converts the dataset into a case, allowing students the opportunity to tackle real-world problems directly.
“I’ve only taken on projects that have managerial implications and can be readily applied in practice,” he said. “Most of my students list these projects on their résumés, which I encourage them to do, because in some cases they’re accomplishing more than they would during a summer internship. Sometimes they come back from an interview and tell me that’s all the interviewer was interested in.”
Kanuri’s practical approach to marketing decision models began when he was working toward his doctorate and attended a conference at the Reynolds Journalism Institute at the University of Missouri, which convened a number of national newspapers. “When I sat in that meeting, I was just baffled to hear that every single problem they discussed was actually a marketing problem,” he said.
He became fascinated with pricing-related issues at major papers and eventually collaborated with a major West Coast newspaper, writing his dissertation on a subscription algorithm he developed that aligned both customer and advertiser preferences. Within six months of implementing a variant of Kanuri’s algorithm, the paper reported nearly $1 million in profits. Suddenly, other departments at the newspaper were eager to work with him.
Kanuri’s interest in the area corresponded with the industry’s increasing reliance on social media platforms, which were proving to be as unpredictable as they were influential. This time, the newspaper solicited his help in determining how to use social media to drive content to the news site. The resulting paper, “Scheduling Content on Social Media: Theory, Evidence, and Application,” was published in the Journal of Marketing and also formed the backbone for one of his course’s group projects.
“How do you go from a model to making a decision for an actual problem? That is the part we cover in class,” said Kanuri. In this case, his students reviewed data comprising the newspaper’s Facebook posts to observe aspects such as the time stamp, title, description, whether the post was boosted and how many link clicks it received. After analyzing the data, the students built a regression model to forecast link clicks and then created a scheduling tool that could demonstrate a correlation to a profit function.
“They’ve really enjoyed the practical aspects of this,” he said. “They get to see both the theoretical relevance and the managerial application of the content we cover in class.”
Beyond the real-world application that the class provides to burgeoning CEOs, Kanuri said it also helps them appreciate the mathematical aspects of business. “Marketing is becoming a more quantitative field, so we explore a lot of mathematical frameworks, not just psychological frameworks,” he said. “It’s inevitable that they will need to pick up these skills, so it’s better to do that when their jobs are not at stake.”
Meanwhile, his research continues. After working with three social media teams at Notre Dame, Kanuri became interested in how color complexity within shared images affects consumer preferences and behavior. In a forthcoming paper, he details how the likelihood of user engagement increases when complex images accompany social media posts. This research in turn led to a different study exploring how people respond to tempo variation in social media videos.
“We wanted to look at characteristics that would affect the pace of content consumption,” he said of the social media video project. “It turns out, higher tempo actually moves people away from the video because it’s a distraction.”
As for future projects, Kanuri does not believe researchers have even scratched the surface in terms of studying social media. “I think a lot of research continues to look at siloed attributes of social media,” he said. “But we understand that one modality is not consumed in isolation, so the research is moving into multi-modal aspects.”
With the rapid expansion of technology, Kanuri is hopeful that researchers in the field will be able to better address a common problem long faced by marketers: attribution. “Marketers are really good at identifying who was there, when and what they consumed on a given channel. But how do you know which combination of factors has driven a consumer to make a purchase?”
Kanuri added that it’s unlikely that researchers will be able to pull consumer preferences from multiple platforms and attribute them to a purchase for at least a few years. “But that’s where we’re headed,” he said. “We want to move beyond a particular platform to get a holistic perspective of content consumption and how content consumption can affect a customer’s journey.”
As his students graduate, they will inevitably encounter dynamics in their industries that cannot be predicted yet. AI-generated algorithms, for example, are already leading marketing managers to contemplate whether they should devote human resources to content generation. For his part, Kanuri is in the early stages of a project that addresses algorithmic design and biases, something he is very passionate about.
Regardless of all the unknowns, he is optimistic about how researchers and students will address the unavoidable changes on the horizon. “I think we should only be threatened when our learning stops,” he said.
Originally posted on Mendoza News.
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