The disruptometer: an artificial intelligence algorithm for market insights
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Universitas Ahmad Dahlan in collaboration with IAES Indonesia Section
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/73880/ http://irep.iium.edu.my/73880/ http://irep.iium.edu.my/73880/ http://irep.iium.edu.my/73880/1/73880_The%20Disruptometer-%20An%20Artificial%20Intelligence.pdf http://irep.iium.edu.my/73880/7/73880_The%20disruptometer-An%20artificial%20intelligence%20algorithm%20for%20market%20insights_Scopus.pdf |
| Summary: | 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. |
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