A case study on the data analytics successes of Netflix came to life with a visit to a Business Analytics class by Andrew Massena, who serves as Senior Technical Project Manager at Netflix. Massena came by at the invitation of Tsovinar Yenokyan, a student in the Master of Science in Integrated Marketing Communications program (’18).
Massena presented on the topic of Marketing Analytics, and the class participated in a discussion about the Netflix Leading with Data initiative. Netflix uses algorithms to help predict user needs and behavior. Visiting Assistant Professor and Director of Math Programs Dr. Nabanita Talukdar (and the class instructor) observes that: “Netflix has thrived because of its superior customer data and analytics. Data analytics gives Netflix the ability to predict what customers might want and provides an understanding of consumer trends.”
What I learned in the class, such as using the R data-analysis tool, will apply to my work on day one.
MS, Integrated Marketing Communications (’18)
Over the last six years, Massena has managed multi-team efforts such as launches in France, Germany, Australia, Japan, and worldwide. His areas of responsibility included ensuring proper catalog encoding and deployment, certifying region-specific configurations, new language support, and App submissions. Last year, Massena managed the effort of Netflix to enable downloading of content to mobile devices. His primary job is running the Netflix NRDP (Netflix Ready Device Platform) Program. He coordinates a cross-functional effort to deliver the latest version of the SDK to device partners (Sony, Samsung, LG, and others) on an annual basis.
Yenokyan says: “I started my own marketing firm in Armenia, and came to the US to expand my career and learn new skills. I want to continue my marketing career, and I need to be able to analyze data no matter where I go. For example, if you have a large customer data set, you need to know exactly who you want to reach. What I learned in the class, such as using the R data-analysis tool, will apply to my work on day one.”
The Business Analytics course’s focus is the practice of business-oriented analytics using statistical methods using the R statistical software. The course introduces analytical techniques applicable for solving common business problems, techniques to analyze social media, and techniques to study data on Web and app users. Students are expected to acquire practical knowledge of computing and interpreting – correlations, confidence intervals, hypothesis testing, t-test, regressions analysis, cluster analysis, statistical significance, run power analysis and compute effect size. During the course, apart from learning statistics and software R, students will be introduced to the concept of Application program interface (API) in the context of data retrieval from Twitter, Facebook, and Google Analytics. Upon the course completion students expected to be able to select the right statistical method corresponding to the business problem. Compute and interpret results of a statistical analysis and produce practical business recommendations.