"My choice of major directly reshaped my future path. During the major selection at the end of my freshman year, I initially chose FIN. However, the POMM course left a deep impression on me, making me realize that business insights attracted me more than financial data. In my junior year, I transferred to the MKT and validated this choice through an internship at an advertising agency. Conversations with senior MKT students further confirmed my fit for a field that combines data and creativity. This shift not only helped me focus on consumer behavior analysis for postgraduate applications but also clarified my ultimate career goals.
In my junior year, driven by the belief that 'MKT students shouldn't just learn theory,' I elected to take courses related to Python. These classes completely transformed my understanding of marketing. The instructor taught using real cases—for example, using Pandas to analyze user behavior data from an e-commerce platform and visualizing conclusions with Matplotlib. For the first time, I realized that coding wasn't exclusive to programmers but was a key to unlocking business problems. I subsequently took courses on statistical modeling with R, learned to apply Structural Equation Modeling (SEM) in competitions, and even self-studied decision trees and random forest algorithms. These skills proved directly useful when applying for the Master of Science in Marketing Analytics and Insights (MAI) at the National University of Singapore. During the interview, a professor asked, 'If you were to use your approach to help Netflix address its current slow user growth, what would you do?' I immediately recalled a group project from a business analytics course where we used multiple regression to analyze Walmart's sales data in the U.S. and found that weather temperature and promotional activities had the highest impact weights. Applying the same logic, I emphasized using data to identify issues with Netflix's online advertising spend. The professor nodded and said, 'That's precisely the practical mindset our programme looks for,' expressing satisfaction with my data analysis skills.
Looking back, my academic background wasn't perfect. I once complained, 'Why can't MKT just be about theory?' and struggled through complex statistical models late into the night. However, it was precisely these 'uncomfortable' experiences that gave me a differentiated edge in applications and my career. If I have any advice, it is this: seize every opportunity in your courses that goes 'beyond the syllabus'—whether taking programming electives or studying topics from other fields. These fragments will eventually piece together into your unique story."