The disruptometer: an artificial intelligence algorithm for market insights - Wan Nordin, Mimi Aminah; Vedenyapin, Dmitry; Alghifari, Muhammad Fahreza; Gunawan, Teddy Surya (Universitas Ahmad Dahlan in collaboration with IAES Indonesia Section, 2019)
Social media data mining is rapidly developing to be a mainstream tool for marketing insights in today’s world, due to the abundance of data and often freely accessed information. In this paper, we propose a framework for market research purposes called the Disruptometer. The algorithm uses keywords to provide different types of market insights from data crawling. The preliminary algorithm data-mines information from Twitter and outputs 2 parameters – Product-to-Market Fit and Disruption Quotient, which is obtained from a brand’s customer value proposition, problem space, and incumbent space. The algorithm has been tested with a venture capitalist portfolio company and market research firm to show high correlated results. Out of 4 brand use cases, 3 obtained identical results with the analysts ‘studies.