Who Should Own Customer Data? Examining the “Data Dividend”

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By: Wise Marketer Staff |

Posted on November 7, 2019

Will paying customers to access their data soon become a common trend?

Close your eyes and picture your perfect customer. Perhaps, depending on your industry, your business, or your loyalty objectives, it is their demographic features which come into focus most acutely. Age, physical makeup, hair color, eye color…or maybe it is their deeper-seated behavioral characteristics that matter most; what kind of culture aspects inspire them? What core beliefs motivate them? Amidst the limitless palette of human diversity, what is held vivid in your mind at this moment is known only to you.

This little exercise helps demonstrate two ideas. Every business has an ideal customer, and the more information and data that is gathered about who they are, the easier it becomes to fill in in the blanks. But where real life differs from an imagined archetype is that actual people don’t exist solely in the mind. And neither does all their personal information. While companies are working tirelessly on the thresholds of current technological limits to craft ideal customer personifications, the clay being used to mold them is cold hard data, some of it very personal indeed. And now, some are saying that in light of rising security failures, sensitivity concerns, and consumer protections, businesses should tangibly pay customers for what some perceive as being rightfully theirs to own.

One of those individuals is Eric Posner. An American author and law professor, Posner claims that data creation is labor, and notes that in the largest technology companies, the share of income going to labor is only about 5-15%. Referring to the general public, who form the rapidly expanding masses of Internet Technology utilization that perpetuates the never ending regime of data creation, dissemination and collection, he posits that “a huge number of people who make significant contributions to the development of AI and other services are unpaid, except roughly in kind, which not only [stagnates] the growth of technology services, but results in a massive transfer of wealth from ordinary people to the tech titans.”

Posner is not alone in this perspective; the general notion is gaining traction not only on the level of individual philosophy, but all the way up to state-proposed legislation. In February of this year, California Governor Gavin Newson proposed a concept known as a “data dividend”. The framework for this idea has been drafted by Common Sense Media, the same organization that spearheaded California's Student Online Personal Information Protection Act in 2014 — it would compel companies who desire to access customer’s personal data for their business operations to pay a financial reimbursements to online users.

“California’s consumers should also be able to share in the wealth that is created from their data…[tech companies] make billions of dollars collecting, curating and monetizing our personal data [and so should] have a duty to protect it.”

As data propagation continues its exponential ascension into the upper echelons of high technology, and as the concerns that have plagued the industry will only continue to be magnified if left unchecked, it is clear that some sort of revolution needs to occur. But is the direct transfer of wealth from the corporation level to the customer level really the panacea that altruists are hoping for? Let’s play devil’s advocate for a moment and take a hard look about some of the claims supporting “data dividends”.

It will increase security

The line of reasoning here seems simple; if companies are forced to pay money, they will naturally be inclined to strengthen their protections in an effort to preserve their financial positions from damage. But companies already have to pay fines for security failures, hacks, and attacks. Weak systems and faulty protections cost companies billions of dollars in direct financial damages. But smart companies (and most companies nowadays are smarter than the press might characterize) realize that lost dollars and cents are not the only harms that befall them for eluding the trust of their customers. Loyalty is valued more now than it ever has been in the past. And customers are fickler now with their corporate allegiances than ever before, turning on entrusted brands for the slightest fault.

There is already an abundance of reasons to deter security problems, yet breaches continue to happen. Perhaps the real reason for their continued presence is that we are overestimating the simplicity of solving the issue and simultaneously underestimating the ingenuity of criminals.

It will encourage customer opt-ins

Argument number 2 for rationalizing data dividends: it will tackle the inherent hesitance of customers to relinquish their personal data over to brands. And while this hypothesis may indeed hold true for a subset of customers, looking at broad demographic averages – the sheer numbers and volumes of individuals which brands are truly concerned with – yields a different picture.

Many customers are already enthusiastic about sending their data off into the information highway, with one big caveat: they expect companies to be transparent with how they’re using it. While research suggests that 79% of customers will depart from a brand if their personal data is used opaquely, 73% conversely state that they would be willing to share intimate information with brands so long as its acquisition and deployment is stewarded transparently.

Does simply paying off customers to use their data make more sense than participating in pro-active relationship building that continues to add value as time passes? Ask any loyalty expert worth their salt, and the answer is unambiguously clear: money is not necessarily the defining epitome of value.  

It provides customers with the value they deserve

This leads to our last supporting argument favoring data dividends: if customers are relinquishing sensitive personal information, information that they create as a tangent to their existence, and information that exposes them to varying levels of risk, then they should receive something of value in return.

Of course, financial restitution is a very direct form of value transfer, one that’s easy to quantify. But is it really the best way of rewarding customers in exchange for getting to know a little bit more about them?

Practically speaking, while data is immensely valuable on a macroscopic level, the individual is cheap. Data takes on significance and importance through the vast aggregated patterns that arise after the analysis of trillions of numbers. If each individual is to be assessed and then reimbursed for their distinct participation, the reality is that the value transferred to these individuals will not be very large. How much money will actually be distributed to the millions of Americans contributing to the ceaselessly voracious data machine? According to Jeffrey Chester, executive director of consumer protection and privacy organization Center of Digital Democracy, the payments may be sized on a magnitude of the order of “a few dollars”.

Instead, how about a system where the value passed on to customers is that of finally being able to crest the next horizon of personalization;

  • Where the exact wants and needs of every customer are swiftly fulfilled, and
  • Where companies can spark lifelong bonds with individuals and develop mutually beneficial relationships to drive economic growth and catalyze overarching prosperity.

Technology has the power to accomplish this. Data has the power to accomplish this. And it’s worth a lot more than just a few dollars now and then.

Regulators and legislators will continue to push for solutions to strike an equitable balance between the perception of value by both brand and customer. Equity will be found in a negotiated position that satisfies the interests of both people and brand organizations. The conversation has merit, but all parties are wise to move at a highly deliberate pace to ensure the solutions found are sustainable over the long term.