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Eunhee (Emily) Ko

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Marketing

We connected with Professor Eunhee (Emily) Ko, a marketing scholar whose work blends quantitative research, data analytics, and real-world business experience. Since joining ÐÇ¿Õ´«Ã½in Fall 2023, Professor Ko has brought her passion for understanding consumer behavior and uncovering patterns in complex data to the Lubin School of Business. With a background that spans analytics training at Northwestern, a PhD from Emory, and hands-on industry and entrepreneurial experience, she equips students with the analytical tools and strategic mindset needed to thrive in today’s data-driven marketing landscape.

Why Marketing?

My academic and professional journey led me to quantitative marketing, where my work centers on data analytics and modeling. I discovered my passion for the field while in the Analytics program at Northwestern University, where I found excitement in learning analytical tools and uncovering patterns in real-world data. This experience inspired me to collaborate with a faculty member on a research project, which led to a conference publication and ultimately motivated me to pursue a PhD at Emory University.

At its core, marketing is about understanding human behavior in commercial contexts. In today’s competitive business environment, the ability to analyze consumer behavior and derive actionable insights is essential for organizational success. Quantitative marketing provides a powerful framework for bridging data, theory, and practice.

Through my research and teaching, I am continually inspired by the opportunity to help students and organizations interpret consumer behavior and make informed, strategic decisions. I enjoy contributing to the field and embracing my role as a scholar and educator in this dynamic discipline.

Why Lubin/Pace?

Lubin and ÐÇ¿Õ´«Ã½offer a unique combination of academic community, practical education, and professional opportunity. The collaborative environment fosters a strong sense of community where faculty support one another and share a commitment to student success. Lubin’s emphasis on application-driven learning aligns with my teaching philosophy, allowing students to work with real data, real business problems, and industry-relevant tools.

I am also excited about Pace’s supportive research environment, which encourages interdisciplinary work and provides resources that help faculty advance meaningful scholarship. The location in New York City offers unparalleled opportunities for industry partnerships, guest speakers, experiential projects, networking, and collaborative research.

Together, these elements make Lubin and ÐÇ¿Õ´«Ã½an ideal setting where I can contribute, grow, and help students prepare for successful careers.

Discuss your professional path and how it informs the way you teach.

My path blends academic training, industry experience, and entrepreneurship—all of which strongly shape how I teach. I completed a master’s degree in analytics at Northwestern University and a PhD in marketing at Emory University, building a strong foundation in data science, quantitative modeling, and evidence-based research.

Outside academia, I founded an e-commerce business and worked on contracted projects with major companies in Korea. These experiences gave me firsthand insight into how analytics, consumer behavior, and digital strategy operate in real business environments.

As a professor teaching courses such as Visual Analytics, Predictive Analytics, and Marketing Research, I draw directly on this background. I emphasize connecting theory to practice through real-world cases, hands-on projects, and industry tools. My entrepreneurial experience fosters creativity and problem-solving, while my research training helps students think critically, interpret data rigorously, and communicate insights clearly.

What are your research interests/areas?

My research spans online marketing and user-generated content (UGC)—including structured and unstructured formats such as text, images, and video—as well as applications of machine learning and econometric methods. I focus on the role of semantic features in UGC and how they influence tangible and intangible asset acquisition for businesses.

My work has been published in interdisciplinary journals such as Computers in Human Behaviour and the International Journal of Research in Marketing, as well as in proceedings from IEEE and AMC conferences.

Why is advancing research in this area meaningful or impactful?

Consumer behaviours have always been quickly changing, especially in this technology-led environment. The consumer behaviours of yesterday might not be the same as those of today, so constant research is essential.

My teaching style is fundamentally hands-on, practical, interactive, and committed to extending learning beyond the classroom.

I incorporate multiple analytical tools and platforms into my courses, ensuring that every student, without exception, develops the capability and confidence to use them effectively in a classroom setting. One example of supporting this goal is that I provide individualized and customized feedback to each student group so they can apply concepts accurately and avoid common pitfalls.

I place strong emphasis on real-world applicability. The final project is a core component in all my courses, allowing students to transfer the skills and knowledge gained in the classroom directly to real business or organizational contexts. My aim is for students to leave my classes with tools they can immediately use in their professional careers.

I strive to create an active learning environment by asking questions, encouraging participation, and designing activities that involve students in the learning process. Engagement is essential for helping students think critically and collaboratively.

Beyond the classroom, I actively encourage students to extend their work by participating in industry or academic conferences, campus events, and external presentations. Presenting to real audiences and receiving authentic feedback provides invaluable experience that strengthens their professional development, much like it did for me during my own academic journey.

What do students learn in your classroom that prepares them for the real world?

In my classes, students develop a blend of technical, analytical, and transferable skills that prepare them for real-world careers. Early in the semester, I include a one-session programming boot camp to ensure that every student, regardless of background, acquires the foundational coding skills needed for the course. This practical introduction to programming immediately equips students with tools widely used in industry, giving them confidence to work with data and analytical software in professional settings.

Throughout the semester, students engage in hands-on, experiential learning. After completing the lecture modules, they work on a final project where they apply the full range of techniques learned in class—data preprocessing, visualization, predictive modeling, and insight communication—to a real-world dataset. This project is intentionally designed to mirror professional analytics work so that students not only practice technical methods but also learn how to interpret results, make decisions, and articulate their findings effectively.

A memorable example comes from a student in my Visual Analytics course who later emailed me to share that she used her class project as part of a job interview presentation. The project helped her clearly demonstrate her analytical and communication skills, and she received an internship offer from a major U.S. company. Experiences like this reinforce my belief that class projects should not be treated as routine assignments but rather as opportunities to build meaningful portfolio pieces that students can confidently showcase to employers.

My goal is for students to leave my classroom with practical skills, strong problem-solving abilities, and a polished project that reflects their best work—something they can leverage immediately as they enter the job market.

How do you incorporate technology or digital tools to enhance learning?

I incorporate technology and digital tools extensively because my courses focus on data-driven methodologies and rapidly evolving contexts such as emerging patterns in consumer behavior. These subjects naturally require students to engage with modern analytical tools and technologies in order to fully understand and apply the concepts we cover.

In my classes, students learn programming languages commonly used in industry for data analysis and visualization. They apply these tools not only in regular assignments but also in their final projects, allowing them to practice real-world workflows and build technical confidence.

More recently, generative AI has emerged as a powerful supplement to traditional analytical tools. I encourage students to use Gen-AI responsibly, while emphasizing academic integrity and clear boundaries around plagiarism. To help them critically engage with this technology, I introduced a new assignment that requires students to experiment with Gen-AI for tasks such as data exploration, analysis, or visualization. The goal is for students to evaluate how these tools can support analytical work, understand their limitations, and develop informed judgment about when and how to use them effectively.

By integrating both established and emerging technologies, I ensure that students gain practical skills and remain adaptable in a rapidly changing digital landscape.

Why is it important to advance research in this area or these areas?

Advancing research in the marketing area is essential because consumer behavior is evolving at an unprecedented pace. With emerging technologies and rapidly transforming purchasing environments, the way consumers shop today is fundamentally different from even three years ago. As digital platforms, AI-driven tools, and personalized recommendation systems continue to reshape the marketplace, marketers must continually update their understanding of how consumers make decisions.

At the same time, new forms of consumer-generated data—ranging from clickstream patterns to social media interactions and mobile behaviors—offer powerful opportunities to uncover emerging trends in the consumer journey. To fully leverage these rich data sources, researchers must adopt new analytical techniques and technologies capable of operating at scale.

For these reasons, marketing research must continually advance. Staying at the forefront of methodological innovation allows us to capture shifting behaviors, understand consumer needs more accurately, and develop insights that are relevant in today’s dynamic environment. Ultimately, advancing research in these areas is critical for keeping the field aligned with real-world changes and for helping businesses make informed, data-driven decisions.

What are some challenges you had to overcome to get to where you are today?

One of the major challenges I faced on my professional path was transitioning into the analytics field. Entering this area required me to quickly learn a new set of technologies and tools for working with big data and unstructured data, skills that came with a steep learning curve. At times, it felt overwhelming to adapt to new programming languages, analytical methods, and rapidly evolving digital tools.

What helped me overcome these challenges was the strong support system around me. I had an excellent mentor in the program who guided my learning and encouraged me to persist through difficult moments. I was also surrounded by talented classmates whose insights and dedication pushed me to grow. This network of supportive peers and mentors provided both inspiration and practical help, making it possible for me to build the skills I needed to succeed.

Looking back, the combination of perseverance, a willingness to learn new technologies, and a strong professional community was instrumental in helping me advance to where I am today.

Of which triumph are you most proud?

The triumph I am most proud of is my students’ success. Nothing is more rewarding than seeing how far they go after completing my courses. Several students have reached out to share their graduate school acceptances, job offers, or internship experiences, and knowing that my teaching played even a small role in their journey is incredibly fulfilling.

One of the moments I cherish most is meeting my students again at graduation ceremonies. Seeing them walk across the stage, confident and excited for the next chapter, reminds me why I chose this profession. Their accomplishments feel like shared victories, and they are the achievements I value most in my career.

What is the single most important lesson you’d like to impart to your students?

Embrace challenge and persistence. I want my students to understand that facing difficulty and continuing to push forward are essential parts of learning and long-term success.

What does #LubinLife mean to you?

#LubinLife means being part of a supportive and ambitious community where students, faculty, and professionals work together to help each other grow. It represents a culture of mentorship, collaboration, and encouragement that extends beyond the classroom.

Classes Professor Ko Teaches

• MAR 222: Marketing Research
• MAR 368: Visual Analytics
• MAR 495: Business Honors Programs Senior Thesis In Marketing
• MAR 635: Marketing Research
• MAR 657: Visual Analytics
• MGT 684: Marketing Research
• MAR 664: Predictive Analytics