The emergence of the Internet has drastically changed various aspects of a firm's operations. Some traditional marketing strategies are now completely outdated,...More >>
The emergence of the Internet has drastically changed various aspects of a firm's operations. Some traditional marketing strategies are now completely outdated, others have been deeply transformed, and new digital marketing strategies are continuously emerging based on the unprecedented access to vast amounts of information about products, firms, and consumer behavior. From Twitter to Facebook to Google to Groupon to iPhone, the shared infrastructure of IT-enabled platforms are playing a transformational role in today's digital age. The Internet is now encroaching core business activities such as new product design, advertising, marketing and sales, creation of word-of-mouth and customer service. It is fostering newer kinds of community-based business models. There is a lot of economic value accruing from the content generated in spaces mediated by social media. There are tangible means for monetization of content through newer forms of online advertising and interactive marketing tools on the mobile web. These processes are just beginning and will have enormous impact on our activities and the way we relate to people and organizations. Traditional marketing has always been about the 4Ps: Product, Price, Place, and Promotion. This course will examine how the digital revolution has transformed all of the above, and augmented them with the 5th P of Participation (by consumers). Management of marketing communications is critical for firms today due to the proliferation of media and channels (including social media) as well as an erosion of traditional business models and cost structures (e.g., for digital advertising). Aside from various Internet marketing strategies and applications, the course will cover the business implications of social media such as blogs, micro blogs and product reviews, social networking platforms, viral marketing, search engine advertising and optimization, digital advertising, mobile marketing, leveraging the wisdom of the crowds such as open innovation, crowdsourcing and crowdfunding. The cases to be used in the course have been chosen to cover a range of industries and transformations of business models over the last ten years, and span search advertising, mobile banking, mobile apps, social media, user-generated content, gaming, crowdfunding, crowdsourcing, and social networking. The objective is to end up with a framework that you will find useful in generalizing across contexts in which information technologies are changing the nature of business and the world.
While there will be sufficient attention given to top level strategy used by companies adopting social media and digital marketing, the focus of the course is also on analytics: how to make firms more intelligent in how they conduct business in the digital age. Measurement plays a big role in this space. The course is complemented by cutting-edge projects and various business consulting assignments that the Professor has been involved in with various companies over the last few years. In addition to assignments analyzing data using Excel, we will discuss:
- Statistical issues in data analyses such as selection problem, omitted variables problem, endogeneity and simultaneity problems, dummy variables, autocorrelation, and multi-collinearity.
- Assessing the predictive power of a regression and interpreting various numbers from the output of a statistical package. Goodness of fit tests and selection of models.
- Various econometrics-based tools such as simple and multivariate regressions, linear and non-linear probability models (Logit and Probit), estimating discrete and continuous dependent variables, count data models (Poisson and Negative Binomial), cross-sectional models vs. panel data models (Fixed Effects and Random Effects).
- Various experimental techniques that help can tease out correlation from causality such as randomized field experiments, A/B testing, and multivariate testing.
We will primarily be using a software package called STATA (available from the Stern Apps server) to analyze data. In order to get the most out of the course, students need to have an understanding of basic regressions and statistics. The focus of data analytics will be on econometrics or explanatory modeling as opposed to predictive modeling. The emphasis of the class will be on doing rather than on reading. In-class time will be spent largely on lectures, demos, guest speakers, in-class and homework assignments involving data analyses using econometrics and HBS style case study discussions.
COR1-GB.1305 - Statistics and Data Analysis