Konnichiwa! (“Hello!” in Japanese) 👋#
Hello! My name is Wakana Morlan, a Marketing Data Analyst/Scientist based in San Francisco. I am passionate about bridging the gap between the art and science of marketing!
I am a data analyst specializing in marketing with 15 years of industry experience. My passion for understanding customers has led me to the unique intersection where the art and science of marketing meet: I identify opportunities from large datasets, build hypotheses, run experiments, and deliver actionable recommendations to marketers and business leaders. With diverse hands-on experience in marketing, a strong foundation in statistical techniques, and proficiency in SQL and Python, I have successfully optimized the performance of various marketing channels.
Remember the movie Moneyball starring Brad Pitt? Today, using data in sports is standard practice, but Oakland A’s general manager Billy Beane pioneered it. The movie taught me that “data wins.” You may not have a large budget or star employees, but if you empower your team to use data to make better decisions, your odds of winning increase significantly. That’s what I do, and it’s what I’m passionate about.
🌈 Empowering marketers to make data-driven strategic and creative decisions. ✨
💡 My Approaches#
Customer First: I believe that making customers happy is the most important step in business. I’ve adopted “Design Thinking,” a problem-solving approach focused on addressing users’ problems and using data to understand customers. I leverage data to uncover insights that even the customers may not be aware of.
Integrated Marketing: I view marketing performance data holistically, recognizing that different marketing channels interact directly and indirectly. Over a decade of experience in managing diverse marketing channels and integrated marketing campaigns allows me to formulate hypotheses and deeply investigate areas impacting business performance.
Experiments: Marketing can often be intangible, but my goal is to make the invisible effects of marketing visible by assigning appropriate metrics. I validate marketers’ “gut feelings” through experiments and observational studies using methodologies like A/B testing, difference-in-difference, synthetic control, matching, and permutation tests.
📊 Experiences#
Industries: Fashion, e-commerce, B2B, Higher Education, Media, Marketplace Marketing Channels: SEM, SEO, Performance Marketing, Organic Social, CRM, Brand, Content, Online/Offline Events, Over-the-top Ads (OTT), Out-of-Home Ads (OOH)
👩💻 Tools and Technologies#
Python, SQL, Tableau, Snowflake, Salesforce, Pardot, Pandas, Scikit-learn, Statsmodels, Scipy, Matplotlib, Seaborn
🚀 What’s Next?#
My long-term goal is to solve complex marketing problems that I have encountered throughout my career. I am particularly interested in building models like Customer Lifetime Value, Marketing Mix model multi-touch attribution model, and customer segmentation.