A robust approach to measure latent, time-varying equity in hierarchical branding structures

By Sudhir Voleti, Pulak Ghosh
Quantitative Marketing and Economics | February 2013

DOI

http://www.springer.com/business+%26+management/marketing/journal/11129

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Citation

Voleti, Sudhir., Ghosh, Pulak. (2013). A robust approach to measure latent, time-varying equity in hierarchical branding structures Quantitative Marketing and Economics http://www.springer.com/business+%26+management/marketing/journal/11129.

Quantitative Marketing and Economics, 2013

Abstract

The literature suggests that brand equity can be split into two parts - an attribute-based equity and a non-attribute based one that captures consumer preferences beyond the utility offered by individual attributes. In addition to measuring attribute-based equity, firms deploying portfolios of products within complex branding structures often seek to measure the presence, distribution and evolution of these potentially heterogeneous non-attribute based unique branding associations - labelled 'residual equity' – at each distinct layer of a product’s brand hierarchy. The authors develop and operationalize a robust and flexible Bayesian semiparametric model to first separate the attribute-based equity from latent residual equity, to jointly estimate this multi-level residual equity and to allow residual equity to exhibit state-dependence using a random-walk prior.
The model is empirically illustrated on syndicated US national beer sales data. The authors find significant, heterogeneous and temporally stable residual equity presence across the brand hierarchy and highlight some substantive implications arising therein.

Keywords: Dirichlet Process Priors, residual brand equity, brand hierarchy

Sudhir Voleti is an Associate Professor of Marketing at the Indian School of Business (ISB), where he is also a distinguished faculty member in Business Analytics. A renowned researcher in the fields of marketing research and business analytics, he has previously served as Associate Dean of Faculty Alignment and the Registrar's Office (FARO) at ISB.

Professor Voleti holds a PhD in Marketing and an MS in Applied Statistics from the University of Rochester, a PGDM from Indian Institute of Management (IIM) Calcutta, and a BE from the Birla Institute of Technology, Ranchi, along with years of industry experience.

Professor Voleti is recognised as one of India's leading data science academicians. His research focuses on combining data with econometric and statistical methods to explain phenomena of marketing interest such as evolution in the equity of brands across time, valuation of brands using secondary sales data, the sales impact of geographic and abstract distances between products and markets, and the performance, productivity, and benchmarking of salesforce organisations.

Professor Voleti has published numerous research articles in leading academic journals such as Management Science, Journal of Marketing, Journal of the Royal Statistical Society, the International Journal of Research in Marketing, and the Journal of Retailing, as well as book chapters and articles in the popular media. He also serves on the editorial review boards of numerous journals. Some of his significant works include "Impact of Reference Prices on Product Positioning and Profits", "The role of big data and predictive analytics in retailing", "Why the Dynamics of Competition Matter for Category Profitability", "A Bayesian non-parametric model of residual brand equity in hierarchical branding structures", and "An Approach to Improve the Predictive power of Choice - Based Conjoint Analysis".

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