Automated Marketing Research Using Online Customer Reviews

Abstract

Market structure analysis is a basic pillar of marketing research. Classic challenges in marketing such as pricing, campaign management, brand positioning, and new product development are rooted in an analysis of product substitutes and complements inferred from market structure.

In this paper, we present a method to support the analysis and visualization of market structure by automatically eliciting product attributes, and brand’s relative positions, from online customer reviews. First, we discover attributes and attribute dimensions using the "Voice of the Consumer," as reflected in customer reviews, rather than that of manufacturers. Second, the approach runs automatically. Third, we support rather than supplant managerial judgment by reinforcing or augmenting attributes and dimensions found through traditional surveys and focus groups.

We test the approach on six years of customer reviews for digital cameras during a period of rapid market evolution. We analyze and visualize results in several different ways including comparisons to expert buying guides, a laboratory survey, and Correspondence Analysis of automatically discovered product attributes. Managerial insights drawn from the analysis are evaluated with respect to proprietary market research reports from the same time period analyzing digital imaging products.

Keywords: market structure analysis, online customer reviews, text mining