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Wiki article
EditBackground
Origins
In the early 2000, prediction markets rose to public fame for the first time, mostly for their highly accurate forecasts of election outcomes. However, early platforms were complex and cumbersome for other market research project types. The initial hype deflated over the next decade.
Enter the next generation
A new generation of system then became available, with vastly improved technology and backed by a rigorous new methodology. These systems offer scaled and discrete question types instead of just a binary Yes/No. They apply action standards and hard benchmarks instead of the original naive 'crystal ball' approach. The best can provide volumetric forecasts instead of just probabilistic predictions. Social conversations and text analysis back all quant foresights with solid qual insights.
Empirical data for Prediction Market vs Market Research Progress
Reliable data on adoption of prediction markets is hard to come by. Only the GRIT report shows at least "claimed" adoption. GRIT reports higher on client side than offers from the agency side, this reflects the significant do-it-yourself portion with inhouse markets.
Google search frequency of Prediction Markets vs. Market Research rose from 3% in 2010 to 6% in 2016. The spikes in search traffic up to 12% in 2016 are mostly due to popular interest in reiiable predicitons for the presidential elections in the USA. Accordingly, searches fell back to lows of 5% after the Trump victory, notably still above the prior levels.
Since then, we saw fundamental growth to a 8% to 9% level in 2018 which indicates rising interest in prediciton market method and technology.
Final Result
The popularity (by search traffic) of "Prediction Markets" has continued to increase since 2016, while "Market Research" is slowly decreasing. The ratio of searches closed on recent high levels at 17.5% as of August 2020.
Sources
- Google Trends
- Greenbook GRIT Report 2016
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