Four years ago, Dutch student Shawn Buckles auctioned off his digital soul; emails, calendars, geolocation, health records and more. The highest bidder bought the prized goods for $480.
Today our data has become more valuable than ever, with monopolies such as Google and Facebook acting like giant internet vacuum cleaners, swallowing records of people’s online activity with ferocity. Meanwhile, new market entrants aspire to capitalise on the fast-growing digital asset by building business models based on consumer ownership of data.
The exponential growth of the Internet of Things combined with breakthrough technologies like blockchain and Artificial Intelligence have led to a gold rush for data monetisation. But how much is our online data really worth?
Over hundreds of years, a new discovery of gold has led to a gold rush, where people rush into an area to mine gold, consumed by the general buoyancy of a free for all in income mobility. People CROWDrush in, in search of the great Californian Dream in which any single individual might become abundantly wealthy almost instantly. For most it turns out to be smoke and mirrors. A few come out rich. Now, the ability to monetise data is spurring a similar entrepreneurial rush into the space.
Monetisation often comes through firms selling your information so that advertisers can better learn the tastes of certain groups. According to recent filings with the Securities and Exchange Commission, Facebook’s average revenue per user in 2017 was $20.21, and users in the U.S. and Canada bring in an even higher sum due to the size of those markets. This means that with 1.4 billion users globally, Facebook rakes in well over $20 billion a year for personal data.
But EY’s Global Innovation Leader for Blockchain, Paul Brody, says that viewing data as the new gold is “a somewhat simplistic metaphor, because in reality, a lot of data is not actually valuable and if you don’t have a good understanding of what you are analyzing, you can come up with all kinds of inaccurate ideas.
“People want to imply that data is more valuable to focus on than physical resources. It means a shift from stuff to information.
“I have a nice chart I can show that gives a nearly perfect correlation between chemistry doctorates awarded in the US and annual cheese consumption. I’m pretty sure these aren’t related in reality.”
So, for those looking to avoid smoke,mirrors, chemistry doctorates, and annual cheese consumption, how does data actually come to be effectively monetised?
“Data on what we read online, what we look at and what we buy or where we go, when combined with a good understanding of what we want to accomplish, can allow marketers to manipulate our decisions and actions very effectively,” says Brody.
“Data, when combined with hypotheses, allow us to test our ideas and know if they really work or not.”
“Assuming you have good hypotheses and an understanding of what you’re looking at, data is the difference between informed strategy and policy-making and just coming up with good ideas.”
“One of the toughest things we’ve had to learn is that not all reasonable-sounding ideas work out in reality.”
As more and more interactions with government, businesses, products and services involve the provision and disclosure of important personal information, there is a wealth of data being generated and collected.
Once this raw data has been processed and analysed, the data holders can then begin to identify patterns, habits, behaviors and trends. This new data can be combined with data from other sources to help identify wider patterns,
trends and behaviors. A bigger picture could then emerge that wouldn’t have been possible in less digital
Companies rely on data analysis for informed decision-making which leads to increased productivity, money saved,
and money earned. They can also use this information to create new products and services and more easily reach a certain target audience. Consumers can be targeted through personal adverts or offers that have been created based on their previous engagement with that particular product or service.
One example could be a supermarket sending a customer an advert for a 20% discount off a certain brand of washing
powder. The company knows from the data that they have collected and from other information that this customer regularly buys this brand of washing powder and that this type of discount will appeal to them.
Data generated products are more likely to have high success rates, as they’re based on real-time information and
analysis of target consumers. With the possibilities for monetising data set to expand in coming years, consumers are slowly waking up to how valuable their data really is; “The ability to combine your information with the ability to measure your reactions and results means your data is, potentially, much more valuable than it has ever been before,” explains Brody. The big question for the future will be “who gets the benefit” he adds.