What are Idea futures?
- Content Type:
- Glossary
Idea futures Definition
Idea futures are speculative markets in which participants buy and sell prediction shares of whatever is trying to be predicted. The current market prices can then be interpreted as predictions of the probability of the event or the expected value of the parameter. Also known as predictive markets, prediction, markets, information markets, decision markets or virtual markets.
Idea futures in marketing research refer to structured prediction markets where individuals or teams "bet" on which ideas, concepts or innovations are most likely to succeed. These markets simulate real-world competitive dynamics to prioritize ideas based on collective intelligence rather than subjective opinion.
What are the key aspects of idea futures as they pertain to marketing research?
- Use of virtual currency or point-based betting on ideas.
- Crowdsourced input, often from employees or expert panels.
- Gamified, anonymous participation to reduce bias.
- Real-time ranking of ideas by perceived value or feasibility.
- Often conducted within innovation pipelines or early product development.
Who relies on idea futures within the marketing research industry?
- Innovation and research and development teams within corporations.
- Market research firms specializing in concept testing.
- Strategy consultants guiding product development.
- Internal insights teams focused on future-facing opportunities.
Why are idea futures important in market research?
Idea futures help filter the best ideas from a large pool by leveraging collective wisdom. They reduce reliance on hierarchical decision-making and improve the predictive validity of idea selection. This method brings greater objectivity and speed to the innovation process.
How do market researchers use idea futures?
Market researchers use idea futures to test new product ideas, messaging strategies or brand concepts by setting up internal markets. Participants are asked to "invest" in ideas they believe will perform best, and the aggregated bets inform decisions about which ideas to prioritize for development or testing.