Teaching
Online Courses and Executive Education
Digital Marketing Analytics
Online Course
Digital technologies have reshaped marketing, leading to a drastic shift in the quality and quantity of information we are able to store, access, and analyze. This proliferation of data allows businesses to better understand and react to consumer patterns. However, it also increases the need to evolve measurement, planning, and implementation of their marketing activity. Companies require skilled professionals who are equipped to ensure optimal return on investment (ROI) for marketing spend, and to deliver valuable insights that drive better customer service. This online program unpacks how to leverage measurement and analysis within your digital marketing strategy. With a focus on analytics-based marketing, you will assess the latest applications of artificial intelligence, machine learning, and predictive modeling that will help drive ROI for campaigns.
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Digital Marketing & Social Media Analytics
In-Person Executive Education
New digital technologies have fundamentally reshaped marketing theory and practice the last decade alone. Technology has changed the modes of communication through which firms engage with consumers. Moore’s law has made the storage and analysis of consumer data scalable, creating opportunities for fine-grained behavioral analytics. New monitoring tools have fostered precise and personalized customer relationship management practices. The rise of mobile phones and tablets has enabled location based messaging and reciprocal communication. The ubiquity of video content has promulgated rich, native advertising programs. The global emergence of social networking has enabled networked based predictive modeling and new forms of targeting and referral strategies based on the preferences of consumers’ peers. And finally, new social media have brought all of this onto the public stage, with word-of-mouth conversations driving brand awareness and brand loyalty, and user-generated content on review and ratings sites making or breaking demand for products or services. This two-day course provides a detailed, applied perspective on the theory and practice of digital marketing and social media analytics in the 21st century. We will cover concepts such as the difference between earned and paid media, predictive modeling for ad targeting and customer relationship management, measuring and managing product virality, viral product design, native advertising, and engaging the multichannel experience. Throughout the course we will specifically stress the theory and practice of randomized experimentation, AB testing and the importance of causal inference for marketing strategy.
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MBA & PhD Courses
Digital Marketing and Social Media Analytics (MBA)
New digital technologies have fundamentally reshaped marketing theory and practice in the last decade alone. Sinan’s Digital Marketing class provides a detailed, applied perspective on the theory and practice of Digital Marketing and Social Media Analytics in the 21st century. It covers topics like Search Marketing, Social Network Marketing, Social Media Analytics, Inbound Marketing, User Generated Content Management and Marketing, Mobile Advertising and Commerce, CRM Strategy in the Age of Big Data and Digital Advertising from the display ad ecosystem to ad retargeting. It teaches the difference between earned and paid media, predictive modeling for ad targeting and customer relationship management, measuring and managing product virality, viral product design, native advertising, and engaging the multichannel experience. The course stresses the theory and practice of randomized experimentation, AB testing and the importance of causal inference for marketing strategy and combines lectures, case studies and guest speakers with relevant industry experience that speak directly to the topics at hand.
Analytics Lab (MBA and Masters of Business Analytics)
The growth in big data and analytics is transforming management decision-making, operations, marketing, finance, and product innovation. Businesses across the world are wrestling with challenges and opportunities that call for the application of analytics. Workers and professionals in all fields are racing to acquire the skills and capabilities necessary to survive and thrive in this digital revolution. The MIT Analytics Lab (A-Lab) guides student teams in delivering leading-edge analytics projects involving machine learning and digital technologies as they apply to business questions and problems. The course offers students an opportunity to roll up their sleeves and “learn by doing” real analytics work for real, cutting-edge global organizations.
Applied Network Theory and Analysis (PhD Seminar)
This course examines the foundations of and recent advances in Network Theory, Network Science and Applied Network Analysis from sociological, economic and statistical perspectives. The course is aimed at doctoral students conducting original research in applied network theory and analysis in a diverse set of fields including sociology, economics, statistics, computer science/machine learning, management, computational biology and physics. The course follows a research seminar format, with deep critical examinations of original research papers from these disciplines, designed to teach networks research through an evaluation of networks research. Topics covered include: network structure, foundations of sociological network theory, weak ties and structural holes, embeddedness, homophily and assortative mixing, information diffusion in networks, small world phenomena, influence maximization in networks, statistical inference in networks, causal inference in networks, networks and coordination, network dynamics, networked experiments, estimating peer effects, networked interventions and more.