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Why Choose? Predictive Market Research Integrates Both Qualitative and Quantitative Methods

In recent years, predictive research methodologies, specifically prediction markets, have gained traction as one of the most accurate and exciting ways to predict future trends, events, and successful ideas. By harnessing collective judgment, asking participants to place bets using virtual currency, and then defending the bets placed with qualitative rationale, prediction markets marry the best features of both qualitative and quantitative research, and in so doing mitigate the biases that compromise the efficacy of more traditional survey methods, leading to more accurate future casting.

“It’s roughly true that in every domain in which we’ve been able to compare data from a prediction market to alternative forecast mechanisms, the market has done better,“ Justin Wolfers, professor of public policy and economics at the University of Michigan, told the New York Times. Prediction markets have become so popular that they’ve spawned what can only be described as a cultural movement in Silicon Valley. 

So, what makes predictive market research so effective? And how can it be leveraged to inform powerful decision-making, from early-stage ideas to product launches? 

 


What is predictive market research?

Predictive market research is a type of research that aims to evaluate new ideas, events, trends, or products to predict the size, scope, and timing of their potential future impact or success within a particular market. As a highly effective behavior-based market research methodology, predictive research is used to predict micro and macro trends, screen and validate new ideas or product and service offerings, and prioritize product features, amongst other applications. 

Predictive market research usually involves the use of an online prediction market, in which research participants are asked to make predictions and bet virtual currency based on their confidence in those predictions. A prediction market incorporates both qualitative and quantitative methodological aspects, allowing for insights into not only what participants predict is going to happen, but why they predict it will happen. 

Predictive market research of this type allows for the measurement of important metrics like judgment, emotion, confidence, and motivation. This results in higher levels of in-market accuracy, deeper insights into consumer behavior, and more accurate foresight into future trends.

 


3 examples of predictive market research in play

Predictive market research has powerful applications for decision-makers looking to optimize their offerings, test new products or services, or capitalize on future trends. 

 

Identifying which idea has the greatest potential

Predictive market research allows decision-makers to test ideas against metrics such as “purchase”, “advantage”, “solves problem”, “meets a need”, “occasion”, and “volume potential”, amongst others, to identify which have the greatest likelihood of success within a particular target market. Through this process, companies can mitigate risk, direct resources to progress and develop ideas that are most likely to work, and maximize ROI. 

Predicting the best mix of features and benefits to drive purchases

Predictive market research can also be used to optimize products or services by identifying the mix of features and benefits that will most strongly appeal to consumers in order to maximize sales. 

Determining which consumer trends are going to hit critical mass, which segments will lead, and when

Predictive market research is a powerful methodology to accurately predict the size, timing, and scope of consumer or category trends, predicting outcomes such as:

 

Will a category grow or decline? 
Which segments will lead trial? 
If, and when, will a trend reach mass?
How fast will sales grow?

With this kind of foresight, companies can capitalize on future trends and gain a significant strategic advantage. 

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3 types of predictive market research methods

Predictive market research tools can vary, but no matter the mechanism, the objective remains the same – to deliver a prediction of the future with the highest degree of accuracy possible. Here are three examples of predictive market research methods that are consistently getting this right:

 

HUUNU Foresight

HUUNU Foresight is a predictive research method that utilizes a prediction market methodology for applications like agile market optimization and the screening of early-stage ideas. The HUUNU platform collects a combination of qualitative and quantitative data from a prediction market, deploying a behavior-based algorithm to calculate likelihood of success. This predictive methodology is superior to traditional methodologies as it often surfaces disruptive or niche ideas that don’t tend to score well in more traditional surveys, but which could result in breakthrough success in-market. 

 

HUUNU Futures

HUUNU Futures is a predictive research future casting methodology designed to predict the size, scope, and timing of future trends and consumer behavior. This predictive research method allows decision-makers to predict things like:


Trend timing, including when a trend will reach critical mass
Trends and jobs, including out-year needs and demand penetration
Brand growth, including emerging or mature growth trajectories 
Consumer behavior, including the magnitude and timing of future behavior

Again, this predictive research methodology uses a prediction market to collect both qualitative and quantitative data to predict not only what is going to happen, but WHY.
 

Predictive surveys

Predictive surveys are a predictive research approach that does not necessarily involve the deployment of a prediction market, but rather predictively-worded surveys designed to extract a combination of qualitative and quantitative data for maximum result accuracy. Participants are provided with topical knowledge and context, then asked to make their best predictions about how they think consumers will react to a product, idea or message. The predictive research design involved in predictive surveys works to minimize over-claim and rational response bias for more accurate results. 

 

 

What’s the difference between qualitative and quantitative research?

Qualitative research collects non-numerical data such as participants’ observations and thoughts and uses this data to reveal motivations, behaviors, and drivers. In predictive market research, this data is collected when participants are asked to give a rationale for the bets they place. 

Quantitative research collects numeric data which is analyzed. This data is structured and is used to quantify preferences and choices, translating numeric data into scaleable insights. In a prediction market, probability scores (e.g., 0-100% certainty) are used to interpret results.


Leverage innovative predictive market research methods at CRG for richer insights

If you’re looking to leverage the extensive benefits of innovative predictive market research design, choose CRG. CRG’s predictive research services have a proven 90% in-market accuracy, three years out and beyond. For over a decade, we’ve been helping insights professionals and marketers optimize their decision-making for unprecedented strategic advantage.


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FAQs

How do I set up a prediction market or a predictive survey that incorporates qualitative data?

Collecting qualitative data in a prediction market or predictive survey is not difficult. The difficulty emerges once that data is collected and it needs to be extracted, structured, analyzed, and interpreted in a way that delivers insights that are both accurate and useful. Partnering with the right service provider equipped with both the technology and expertise required to get this right is paramount if you want to unlock the wealth of benefits associated with qualitative research. 

What makes predictive market research preferable to traditional survey methods?

There are a number of benefits to predictive market research which make it superior to traditional methodologies. First, it is faster, more cost-effective, and highly accurate. Additionally, the inherent nature of a predictive exercise – the fact that participants are asked to predict how others will behave within a supplied context – mitigates various biases that normally skew traditional survey responses. In short, the results you receive from a predictive survey more accurately reflect reality.

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