Editor’s note: Paul Neto is chief marketing officer at computer software firm Measure Protocol, London. 

Today, consumers are demanding more control over every interaction they have, and nearly every interaction results in data: where they go, what they’re purchasing and who they’re communicating with. All this data has value when companies are determining important business decisions. So how long before consumer demands for control over this data starts to increase exponentially? 

With the advent of regulations like GDPR and huge corporate pitfalls like Marriott’s giant data breach, consumers are beginning to wake up to the value of their data. They want control, privacy and security and, in some cases, they don’t want to give this important information about themselves away for free. 

This new reality has a direct effect on market research, which depends on centralized databases from which to draw for potential survey respondents. Specific demographics can be searched and targeted because the information is centrally available. For consumers, this means that their data is intrinsically insecure, or at least susceptible to large-scale data breaches that we’ve become too accustomed to in the news. Consumers have no control over their data or how it’s used. Does this disconnect equal a negative impact on quality outcomes in the long term? It’s likely. 

The tension over data ownership is now taking its place alongside recurring challenges in the market research space such as poorly designed surveys, declining respondent participation and dismal data quality. These are symptoms of an industry that is ready for change. 

Two approaches 

Storing user data in a centralized database comes with benefits including cost and convenience. This approach also encourages organizations to hoard and collect all and any data they can get their hands on. With the rising sensitivities and risks of storing user data, we must look at new philosophies and methodologies around data collection.

There are two possible approaches to this: practicing data minimalism – only collect what you need and if you’re not sure if it is necessary, don’t collect it; and absolving oneself from direct ownership. 

We’ve recently gone through an era of big data. The objective was to collect anything and everything and let the big data machine figure out what is and is not important. This was partly accelerated through the efficiencies and cost savings of storing data in a centralized manner, leading to hoarding data “just in case.” The reality is that every bit of data collected about an individual is a liability. While businesses still must run and utilize data, it then becomes imperative that we take real efforts to become data minimalists – collect only what you need.

Data minimalism requires a change in the philosophy surrounding data. It must shift from “let’s collect what we can while we can”, to asking a few serious questions about each and every piece of user data. We must start to see the entire process from the user perspective. For each and every piece of data collected, an organization must ask itself questions like: 

  • Does this piece of data help drive a business outcome? 
  • Is it in the best interest of the consumer that we store this data? 
  • What is our comfort/discomfort level with being transparent on collection and use of this data? 

Similarly, it’s important to consider the liability of obtaining a piece of data. What if there is a data breach? Are we equipped to address right to access or right to be forgotten legislation?

Our appetite to hoard data will start to minimize if we can collectively align motivations and incentives for sharing data, both for consumers and organizations. If we can successfully build an ecosystem of trust using blockchain, cryptography and other technologies and processes, the barrier to sharing data should decline and the willingness to share data should increase. The net result is access to more data of greater quality versus vast warehouses of noisy data.

The second approach to data collection is absolving oneself from direct data ownership. A primary way that consumers can take back control and security of their own data is by storing it on the edge or on their own devices. By keeping a tight rein on their data, and keeping sensitive information out of databases, this changes the game not only for them (they are better able to monetize their data and choose who uses it) but for researchers. Now the focus shifts from taking measures to keep the database-stored data secure, to finding new ways to connect with the respondents for engaging, sharing data and participating in research. 

Sampling on the blockchain

Without having direct access to a consumer’s data when it is fully encrypted on their device, how can we request and confirm that they qualify for a study with confidence? One answer is to look to cryptographic techniques that have emerged with renewed interest and relevance since the growth and popularity of bitcoin. Cryptographic techniques such as zero-knowledge proofs is a method by which one party can sufficiently prove to another party that it knows a secret (a value), without conveying any information apart from the fact that they know the secret. For market research, this means you can qualify someone without revealing any unnecessary information. In this manner, privacy is maintained, consumers are given a choice to participate and odds of their doing so is boosted by a fair incentive.

The opportunity

Employing blockchain and cryptographic techniques focused on protecting the consumer, their data and establishing fair rules of engagement essentially provides an opportunity for the industry to reset motivations for how and why consumers engage. Because privacy of personal data and transparency of the research process are built-in by design, this directly addresses consumer concerns over data control and privacy. While we have legislation such as GDPR helping consumers regain rights over their personal data, to future-proof our industry, we must go above and beyond – this includes adopting a data minimalist approach and removing ourselves from the data storage function. Although this approach will require a change in the industry, it certainly comes with the promise that building consumer confidence and trust will result in heightened data quality and better outcomes.