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Personal Data: The Ultimate Commodity?

Personal data has been described as the "new oil" that will drive the economy of tomorrow, but it's being treated as a commodity rather than a precious resource. We need to start developing models that incentivize and reward individuals for contributing to the data economy.

Recently, John Thornhill wrote an interesting article in the Financial Times on the role platforms like Facebook can play in establishing a universal basic income via data. Here is the crux of his argument:

“The most valuable asset that Facebook possesses is the data that its users, often unwittingly, hand over for free before they are in effect sold to advertisers. It seems only fair that Facebook makes a bigger social contribution for profiting from this massively valuable, collectively generated resource.

His shareholders would hate the idea. But from Facebook’s earliest years, Mr. Zuckerberg has said his purpose has been to make an impact rather than build a company. Besides, such a philanthropic gesture might even prove to be the marketing coup of the century. Facebook users could continue to swap cat pictures knowing that every click was contributing to a greater social good. “

In 2011 The World Economic Forum classified personal data as a new Asset Class along with property, investments, cash, etc. This laid the foundation to rethink how data can be utilized to deliver value to the owners and originators, not just the users. In the original report issued by WEF and Bain, they call out both the technical and philosophical challenge:

“At its core, personal data represents a post-industrial opportunity. It has unprecedented complexity, velocity and global reach. Utilizing a ubiquitous communications infrastructure, the personal data opportunity will emerge in a world where nearly everyone and everything are connected in real time. That will require a highly reliable, secure and available infrastructure at its core and robust innovation at the edge. Stakeholders will need to embrace the uncertainty, ambiguity and risk of an emerging ecosystem. In many ways, this opportunity will resemble a living entity and will require new ways of adapting and responding. Most importantly, it will demand a new way of thinking about individuals. Indeed, rethinking the central importance of the individual is fundamental to the transformational nature of this opportunity because that will spur solutions and insights.”

We have come far in developing the technologies that can enable the management of personal data in a trading environment. In fact, Blockchain shows great promise as the underlying architecture to power the trading of data as a type of cryptocurrency and is rapidly evolving as a transformative model for transactions. AI and “Big Data” models have largely addressed the type of analytical frameworks needed to combine data sources, and the marketing world advances in attribution, single-source, and programmatic ads have proven we have the systems to use personal data to deliver highly targeted content (in the form of ads and recommendations) in almost real time based on the digital treasure trove of data available.

However, and as John Thornhill pointed out, today consumers’ data is simply used without direct reward to the consumer. It’s a barter system: “let us use your data so we can try to sell you more stuff, and in return you get access to these nifty technology platforms.” That has been fine, but it’s a far cry from treating data as an asset class that can generate real financial gains for consumers — not just value.

What is missing is not just a shift in thinking, but also a fundamental reshaping of the value exchange. In short, we need to stop treating data as an easily accessible commodity and start paying for it as a precious resource. We need incentives and rewards to help kick-start a new system.

Fundamentally, people do things because they get something out of it: we take action because it fulfills a need, whether it’s conscious or unconscious. This core motivation is central to every school and application of behavioral science. Game Theory and Behavioral Economics specifically have taught us that a system of incentives and rewards are necessary to engage humans. In general, this system can be boiled down to a few key categories:

  1. Social: Connects us to others for fun and social interactions. Think of all the games on Facebook or online game networks.
  2. Financial: Delivers a direct financial reward such as research incentives, discount or deal networks, personal data lockers or recommendation systems.
  3. Values: Altruism, charitable causes, political or social campaigns and anything else that is aligned to our values.

The ideal system combines all of these. The market research industry has actually pioneered quite a few examples in action via the advent of online communities, and there is much from that model that could be applied throughout the research industry in support of a personal data economy. This system looks something like the example below:

  1. A brand wants to engage in a long-term dialogue with a subset of consumers to explore new product ideas.
  2. Participants are identified via profiles established in panels or in social media.
  3. Targeted consumers are recruited and paid a financial reward for engaging.
  4. Exercises are “gamified” and participants are sent on missions, earn badges/rewards and discuss their ideas and the ideas of others in forums within the community.
  5. Results are shared back so participants can see how their contributions help create new solutions to issues that impact their lives.

This approach to creating a real, engaging motivational framework for consumers to share their data is a good example of how we can rethink the value of personal data and how people can gain more than just access to apps for its use. That model of value-exchange is proven and has created value for all parties involved — but it has limitations.

A multi-dimensional system that has real incentives and rewards that pay consumers for their participation in an accretive way is not only more fair — it also drives the shift in necessary thinking to support the emergence of the personal data economy. Whether it’s getting a “data access annuity” from Facebook or Google, direct compensation for participating in research or data analysis initiatives or receiving goods and/or services as a “lease” on consumer data access, each model has incentives at their core.

No longer a tactical afterthought, consumer rewards are the tip of the spear in leading a transformation in how consumers use their data for their own benefit vs. others using it for personal gain. Direct reciprocity simply changes the game.

Incentives solution providers today are inherently “fintech” companies. My friends at Virtual Incentives for example use a robust enterprise API system to deliver real time, customized reward options from scores of partners through multiple consumer channels. They are a combination e-tailer, bank and stock exchange, processing millions of transactions at scale — all driven by consumer demand. That kind of technology is a vital key component of building the personal data economy, and the thought leaders behind it need to be part of the debate on what the future should look like.

The debate around personal data ownership and value, alternative and universal income schemes and the role of technology in making it all happen will continue to be important topics over the next few decades. However, incentives and rewards won’t just be a big part of that dialogue; they have already gone far in solving many practical issues.

Building on their firm foundations, the future of the personal data economy looks bright indeed.

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8 responses to “Personal Data: The Ultimate Commodity?

  1. If personal data is the new oil, and Facebook / Google / Amazon are the new Exxon / Halliburton / Aramco, in what scenario does it make sense for any of those organizations to donate their wealth to the masses? Rail barons aren’t exactly known for their largesse.

      1. Also, in the new business models being developed, or yet to be developed, these large companies will co-exist with personal data brokers. They will benefit from the authenticated data coming from other sources for sharing their’s.

  2. It would be lovely if fair counted for very much. But, if fair did count for much in the wider world, there are plenty of more pressing needs than data (like ensuring everybody in the world had clean drinking water).

    Data is going to evolve in several directions, and in different countries, this will have different results. The first split I will mention is Europe vs USA. When banks (and other data-rich entities) were invented society could have said the transactions information was ‘owned’ by the bank or ‘owned’ by the individual – neither is more right than the other. Europe has the model of individuals owning data and companies being allowed to use it, and USA went with banks owning it. These differences are going to run into a major clash over the next few years.

    Another interpretation is that society owns the information. In China, most people’s photos are stored on government computers and used for regular things like ID cards, but are also integrated with facial recognition cameras, the result being that when you jaywalk you get sent the summons, because of automated AI systems (like the minority report, but not focused on retail).

    There will be some data as currency, for example, panel members who say sure, give me $10 a year and you can passively monitor my watch, phone or whatever. But this will be the tip of the data iceberg.

    The two big trends, IMHO. The first is more of the Facebook type approaches, we will give you some great ‘free’ services if we can collect and sell your data – and that is a value exchange. The second will be legal restrictions on what can be done with the data, more security (e.g. reactions to Equifax), more rights (e.g. the right to be forgotten), limitations on what data can be used (e.g. we may ban the use of DNA data in the calculation of insurance premiums), and much greater use of data by the state to reduce crime and terrorism (and possibly even antisocial behaviour).

    One of the reasons that data is not going to be a significant currency for individuals is that the value of one person’s data to other people is pretty low. What makes data valuable is having lots of it, from lots of people. So, Facebook’s data is really valuable, but divide that by 1.3 billion users and it is not so much per person, and if one person were to opt out from Facebook data is worth the same. The value of most things is determined by the marginal buyer and the marginal seller – and if Facebook were to add or lose 100,000 users it would change the value of the database very little.

    1. I think we’re both right (kinda); your point about the differences by country is an important one, as is the value of data in the aggregate. However, in the world of one-to-one, individualized programmatic marketing that dynamic does change and the worth of an individual data profile can be significant. Think of it as buying power; if a consumer spends $1,000 a month on Grocery/CPG items (about right for my family), what is the value of my data to the brands who want to sell to me directly? $100? The emerging model of individual, data-driven marketing means full attribution and ROI modelling, and if the brands is paying for the privilege to sell to someone by using their data and it can be shown to manifest in purchase, that clearly has a real value to the marketer. Today the marketing platform sets that value of that and collects the money, but the idea I am proposing is that it really should be a revenue share between the platform and the consumer.

      1. By the way Ray, I think this general topic is something we should explore via future NewMR, IIeX, and blog posts! It’s a big, complex topic that does have big implications for MR and society as a whole. I’m glad you are sharing your views to help prompt a good discussion!

  3. Hey Leonard, great article and I totally agree personal data (the highly valuable resource we all constantly generate) can be the key to establishing concepts such as a universal wage, new frontiers for innovation and significant upgrades to our healthcare and education system.

    I work for a company called PI.EXCHANGE that looks to do just this, we layer the data exchange above a machine learning system in order to automate the production of insights – thus also democratising data for businesses (accessible to businesses of all sizes). We feel this is how we can best augment the value of personal data sufficiently due to the resulting increase in demand.

    We recently released a beta app on iOS and if anyone is interested, give it a shot and give us all the feedback/ issues you find – its 100% free and we are building something that I really feel can benefit our planet.

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