Market research is broken. Here’s how blockchain fixes it.
Market research is tough. The best data companies conduct a combination of primary and secondary research to draw data from experts and consolidate information from national and international organizations. This process of getting information is challenging for several reasons.
First, each company is spending substantial resources to recruit and consult with experts. Since companies are all seeking the same information, it leads to a duplication of effort. Second, individual analysts covering multiple geographies cannot possibly understand all the nuanced regional socioeconomic factors affecting markets of interest and this is further exacerbated by language barriers and time zone differences making it difficult to communicate with more knowledgeable parties. Third, most developing countries with high growth potential do not have comprehensive registry on epidemiology data or procedure volume, leading to suboptimal market forecasting. Fourth, there are no established standards for comparing forecast numbers to real world data post-publishing, leading to forecasts that are believable but not neccessarily accurate. Lastly and importantly, there is currently no mechanism for market research firms to collaborate in a way that improves forecast results. A new technology, blockchain might change all this.
There are no established standards for comparing forecast numbers to real world data post-publishing, leading to forecasts that are believable but not neccessarily accurate.
The blockchain, a distributed ledger technology, that has emerged in recent years, popularized by the meteoric rise of digital assets like Bitcoin and Ethereum, offers a unique solution to the problems faced by market research organizations. In particular, these assets have the distinct quality of enabling “smart contracts” which are self-enforceable and could bring significant advantages over existing frameworks for market research data collection. The blockchain facilitates the addition of timestamped entries into a ledger maintained by a decentralized set of nodes resulting in desirable features such as immutability and transparency. The key innovation enabled by a blockchain-based approach is the efficient collection and verification of data, as well as incentives for accurate data. It also establishes an immutable record such that forecast accuracy can be back-tested at a later date.
The system would work like this: utilizing a decentralized prediction market, a market research firm will ask a question such as “What will Stryker’s gross revenue for total knee replacement be for 2017?” Then, with a digital identity verification service, the firm will create a network of subject matter experts and issue “ tokens” to each participant. Participants will be chosen based on their professional credentials, education experience or job history. The experts can then make a prediction by putting some of their tokens at stake. At the end of the prediction period, one of two things could happen; either a pre-designated oracle verifies the correct number or the average of all submissions is taken and participants are paid out depending on the accuracy of their guess. Accuracy could be determined using standard deviation from the average or a more sophisticated yet-to-be determined algorithm.
Prediction markets are poised to become a disruptive innovation in data science, and with the invention of powerful peer-to-peer computing technologies, the scientific exploration of market-based forecasting can proceed uninhibited at a rate and scale previously unimaginable. This new ecosystem will reduce costs, align incentives, and disrupt the current means of acquiring competitive intelligence. Organizations that have invested heavily into creating expert networks will have the opportunity to monetize their processes both inside and outside their core business areas. It places a higher premium on accurate analysis, and key opinion leaders (KOLs) can more easily monetize their expertise. Information drawn from these and adjacent markets could be used as an input to inform more advanced real-time predictive decision-making models in finance, government, insurance, consulting, and beyond. In addition, data scientists leveraging artificial intelligence could integrate into this system and improve forecast results.
The tools to accomplish all these exist or are in production already on platforms like Ethereum and Rootstock however, there are still barriers to effectively executing this plan. Ethical concerns that such a platform will create an avenue to profit from the sale of insider information need to be addressed. However the success of platforms like PredictIt (a prediction market for politics) and the interest in blockchain projects such as Augur give credibility to the idea and its possible application to niche fields such as healthcare. Also, due to the limited research in these technologies, there lies an unknown attack surface that a malicious entity could exploit to bring the whole project down. There is also the risk of a major event, regulatory or otherwise, stalling the growth or impeding the feasibility of the technology . That being said, this is a promising frontier for a new breed of market research firms using crowdsourced data and cryptographic technologies to create decentralized forecasting and resolution strategies.