Visualizing Asymmetric Competition Among Over 1,000 Products Using Big Search Data

Understanding competition is essential for every firm. Unfortunately, information on who competes with whom is scarce. Traditional research approaches such as surveys and panels are time consuming, expensive, and not applicable to markets with large numbers of consumer durables. Big search data from websites, however, reveal which products consumers consider to be “competing” alternatives. We propose a new model that uses big search data and combines methods of multiple research disciplines to analyze and visualize asymmetric competition in durable categories containing more than a thousand products. We demonstrate our method by analyzing and visualizing asymmetric competition among 1,124 LED-TVs. We externally validate our findings with actual market shares and find that product- and price comparison site data provide higher external validity than data from Google and Amazon.