The ongoing economic reforms and globalization of the Indian economy have led to dynamic and continous change in Indian markets. Markets are becoming more competitive and diverse. faced with greater choice, consumers are becoming even more demanding. Consequently, taking key marketing decisions has become more complex,especially those related to market segmentation, product positioning, offer design, pricing and test marketing.
At the same time, availability of information on Indian markets, product offerings, and consumer preferences and choices is also increasing. Multivariate statistical tools for data analysis like regression analysis, factor analysis, discriminant analysis, conjoint analysis, multidimensional scaling and structural equation modeling can effectively be used in making these decisions. Data and text mining approaches are also becoming increasingly relevant for understanding customers, segmenting them and devising strategies to attract and retain them.
This programme has been designed to help participants acquire skills in using multivariate statistical tools in taking the key marketing decisions. It also exposes participants to the data mining and other approaches to statistical analysis of the data that is increasingly becoming available, particularly in retail, telecom and finance and in many other sectors.
Expose participants to a selected set of multivariate statistical tools and data mining approaches that would aid in taking key marketing decisions: market definition and choice of markets, market segmentation and targeting, product positioning, offer design, pricing, and test marketing.
Provide participants an opportunity to gain experience in using latest PC-based statistical software in concrete marketing management situations.
Introduce key concepts of data mining.
Marketing Decisions: Choice of Markets, Market Segmentation and Targeting, Product Positioning, Product/Offer Design, Pricing and Test Marketing.
Tools for Analysis: Forecasting Models, Multiple Regression, Discriminant Analysis and Logistic Regression, Factor Analysis, Cluster Analysis, Multidimensional Scaling, Conjoint Analysis, Structural Equation Modeling, Models for Pre-test Marketing, Classification and Partitioning, and Data and Text Mining approaches.
Managers in charge of strategic marketing planning, product management, promotion and advertising, and marketing research in companies marketing consumer or industrial products or services.
Account executives in advertising agencies.
Professionals in marketing research and data analytics organizations.
A three-fold methodology has been designed so that participants would acquire skills to define a marketing problem, use software for statistical data analysis and data mining, and use the results from the analysis for making marketing decisions.
Firstly, the class sessions involving discussions of cases and sharing of experiences would help in defining problems, understanding data analysis, and its use in decision making.
Second, participants would work in the PC lab on small data sets to get hands-on experience in learning the use of data analysis software of specific techniques.
Lastly, working with fellow participants on a real life project would help participants in understanding and applying relevant data analysis techniques and using their output for improved decision making.