Ram Janakiraman

Education

Ph.D. Business Administration, University of Southern California

Courses taught

MBA 565 Marketing Analytics
MBA 590 Machine Learning and Marketing

Area(s) of focus/expertise

Substantive: Digital/Social Media, Multichannel Marketing, Retailing, Big Data in Marketing, Healthcare Analytics/Healthcare Marketing, Marketing and Public Policy.

Methodological: Applied Econometrics, Quasi-Experimental Methods, Structural Learning Models, Consumer Choice Models.

Research interests

I use machine learning models and applied econometric methods to understand customer behavior in various contexts such as retailing, social media marketing, public policy, and healthcare. I combine state-of-the-art tools with novel granular-level data, and structured and unstructured data in my research to offer insights to managers and policymakers on customer and consumer behavior that can aid them with optimal decisions.

Recent/past research

In one of my recent research, we examined the effect of online reviews on hotel bookings. We developed machine learning models on both structured and unstructured data to examine the effect of online reviews of a focal hotel and that of its competitors on hotel revenues. The study offers important insights into hotel revenue management. In another recent research, we examined the effect of change in clock from standard time to daylight saving time on consumers’ unhealthy behavior. We developed a model based on quasi-experimental research techniques and novel consumer-level data to document the onset of daylight saving time on consumers’ unhealthy behavior and we offer important recommendations for firms and policymakers. 

Experience with industry (and how it informs what I teach)

I interact and work with a number of organizations in various industries ranging from multichannel retailing, hotels, grocery retailing, and healthcare. Interactions with practitioners give me the opportunity to pursue research questions that are of value to managers and also help me get access to novel data to provide data-driven answers to those questions. I provide students with access to novel and big data that helps them learn various machine-learning techniques.

Why students may want to study marketing analytics

We are familiar with the quote that data is the new oil. I tell my students that oil becomes more valuable when it is refined and in a similar way, data becomes more powerful and is a competitive advantage when it gets refined and converted to information and insights. Marketing is becoming more quantitative, thanks to rich customer data that brands and retailers are able to capture. There is a great demand for students who can help firms and brands convert such data into usable information. Marketing analytics helps students acquire these valuable analytical skills.

Highlights of teaching for the program

I cover a number of analytical techniques in the marketing analytics and machine learning courses I teach. The students work on an analytics project in which they get to learn how to implement a machine learning or analytics project on real data. I teach students how to implement analytics with both coding and no-coding interfaces.

Advice for prospective students

There are several tools and software available to implement analytics. My advice to students is to pick one of the tools (software) and spend time learning it to get comfortable enough to apply it to any analytics problem. There are several online resources available to learn these tools. The Master of Management, Marketing Analytics program does a terrific job in teaching these tools as well. I would also recommend students take courses that teach different types of quantitative methods.

Why Choose the Master of Management, Marketing Analytics (MMA)?

The Master of Management, Marketing Analytics program teaches all the practical tools for those students who are interested in careers in both marketing and analytics. The program teaches several state-of-art techniques to students. Our students have a wide variety of backgrounds and the program does a great job of teaching both the technical and strategy aspects at the intersection of marketing and analytics. 

Something personal you would like to share?

When I am not thinking about teaching and research, I enjoy watching and following cricket and tennis. Recently, the U.S. market was introduced to cricket in a big way with the World Cup being hosted by the U.S. and the U.S. cricket team did well to get to the second state. I see sports are becoming data intensive with coaches and players in different sports using analytics to develop strategies and game planning.