Visualizing the Competitive Structure of Online Auctions

  • Authors:
  • Stephen France;Douglas Carroll

  • Affiliations:
  • Lubar School of Business, UW --- Milwaukee, Wisconsin, 53201-0742;Graduate School of Management, Rutgers University, Newark, 07102-3027

  • Venue:
  • ICDM '09 Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects
  • Year:
  • 2009

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Abstract

Visualizations of product competition are common in marketing research. Competitive product relationships can be modeled using data from a variety of sources, including questionnaires, surveys and brand switching data. Product competition applications based on brand switching data are usually restricted to high volume, frequent purchase products such as coffee and frozen foods. Analysis of competitive product structure requires data for multiple purchases from a single consumer, data that are not usually available for large value, rare purchase items such as cars and computers. We use bid information from online auctions as a source of competitive product structure information for these items. We develop a simple algorithm for creating a distance matrix representing market structure between brands and brand features from online auction data. We take data from eBay mobile phone auctions in the USA and based upon the auction data develop visualizations of product competition for brands and brand features.