Sharmistha Sikdar currently teaches the Thayer MEM Marketing core within the Master of Engineering Management (MEM) program. She also teaches a Tuck elective course called Marketing Research and Analytics for Data-driven Growth. See below for course descriptions.

Thayer MEM Marketing

This course introduces the role of marketing within business firms. Case studies drawn from a wide variety of consumer and industrial products and services provide an opportunity for students to apply concepts and techniques developed in assigned readings. Specific topics include customer analysis, market research, market segmentation, distribution channel policy, product policy and strategy, pricing, advertising, and sales force management. The course stresses oral and written expression and makes use of several computer exercises, spreadsheet analysis, and management simulations.

Marketing Research & Analytics for Data-driven Growth

Most decisions in marketing are characterized by significant levels of uncertainty. Some of these decision-making instances are new market entry, new product or service development, product pricing etc. Marketers can control for the uncertainty around a decision making with appropriate research and data analysis. Market research and analysis enables marketers to understand and predict evolving customer trends and anticipate competitor response.

This course provides a managerial introduction to market research and analysis methods that can help managers with the following:

i) Translate marketing decision problems into questions amenable to research and analysis.

ii) Scope out the problem and determine the research design.

iii) Identify sources of data and appraise these on cost and quality considerations.

iv) Identify and utilize the right methodology and analysis toolkit for the research question at hand.

v) Interpret results from the analysis and develop recommendations for marketing action.

This course encompasses the traditional market research methods intended for short-term decision making (e.g., new product design or addressing a service complaint) and introduces predictive analytics that provide insights for long term decision making (e.g., lead generation, post-marketing campaign tracking). The course is intended for those who want to pursue a career in marketing research, product marketing, marketing analytics, and data science. This is primarily a methods class with emphasis on hands-on training through in-class workshops. The course will use R as the main programming software, Sawtooth Software for conjoint analysis, PERMAP for perceptual maps.

The course covers the following methods:

• Survey and questionnaire methods
• Data cleaning and preliminary analysis with crosstabs and chi-squared tests of association
• Understanding customer sentiment with textual analysis
• Understanding customer’s choices with binomial and multinomial logit models
• Translating customer choices to product design with choice based conjoint analysis
• Segmenting the market with cluster analysis and identifying appropriate target segment
• Understanding product positioning with multidimensional scaling and perceptual maps
• Lead generation and post-launch campaign tracking with predictive models (overview): logit, random forests, gradient boosted trees.