Is Data really a currency?

When people discuss currencies they tend to think of paper notes—American dollars, Japanese yen, euros or pounds. Printed money, however, is only one kind of currency. Currencies have evolved over time from stones and seashells to the sophisticated forms of legal tender that enable today’s global financial transactions. The evolution of currency continues today as new, alternative currencies grow in popularity.

In this new digital world expectations are increasing. Today’s customers demand products and services that are personalised, reliable and durable, at the times and in places they want them. Thanks to the large amounts of data being made available by the billions of connected devices out there, it’s easier than ever for businesses to meet these expectations. It’s because of these developments that data is believed to be the new currency.

Data has become more valuable than ever, with the increased use of social media and the internet for everything from: research, connecting with others, and shopping to running and promoting a business, and data mining. Companies are utilizing data from several sources to target people with advertising that appears coincidental, yet is based upon hours of data. In this internet savvy world data is the newest currency on the market and it is creating value from what some may perceive as junk.

To understand how data fits into this evolution we must rethink our conception of currencies. Currency is how we create and exchange economic value across geography and through time. It is anything that can serve as a medium of exchange, something that can be “cashed out” for goods and services, or used to pay a debt or to store value for future use. Data has each of these essential characteristics. Because many business transactions involve buying and selling data, it can serve as a medium of exchange – as a young musician said, instead of sending her royalties, streaming music services should provide her with data about her listeners.

Web browsers, such as Google, are analysing the habits of its users constantly. The search engine then stores this data, relating to people’s browsing habits, and sells it to their advertisers. The advertisers are then offered the opportunity to have their ads appear on web pages that support advertisers. For instance, if a user is shopping for a child’s bedroom set and then decides to head over to Facebook to ask a question to the mum group she belongs to, an advertisement for a children’s furniture store could appear on her Facebook account. The user will think it is just another random ad, however, it is a strategically placed, targeted ad, based on her online shopping habits that day.

The value of data can also be measured easily, as many of today’s most successful companies have demonstrated, as data appreciates in value when translated into meaningful information. For instance, it was estimated that retailers would be paying major US banks $1.7 billion a year in 2015 to send targeted discount offers to customers based on information on shopping habits gleaned from credit card records.

Aggregated data from internet browsing and social media profiles has become a line of revenue for many companies. The advertising arms of search engines and social media sites can sell consumer data to advertisers as this ensures increased traffic to the advertiser’s website. Advertisers in turn use this data to raise their revenue because they can ensure more qualified leads. All the while the user is being guided, based on their usage and habits, to websites and retailers that appear to be at the top of the buyer’s needs and wants list.

Beyond reviewing your customer base’s search history and buying patterns, social media companies are aggregating personal data from their users to help direct your marketing efforts. Users of Facebook, Twitter, Instagram, and other social media sites provide data including: age, location, family size, employment, education, interests and likes to the companies to be more transparent. However, this data becomes a tool with which the advertiser can target their audience specifically, saving time and money. This data has become a large stream of revenue for social media, allowing marketers to target the specific audience required for each campaign.

The simplest mobile phone call is a miniature data gold mine. Two people talking on their mobiles only think about their conversation, but as they chat data is being collected about their location, the time and length of their call; possibly even the way that this data correlates to their other digital activities, online or social Everywhere we turn we leave behind “digital breadcrumbs,” and advertisers and service providers are “churning through thousands of bits of data to figure out what offers to give each of us next, and at some point, your content and experiences begin to be managed.”

We should face the fact that if humans are in the process chain, it is not going to be possible to keep financial track of all the services created on the fly by systems in real time. One of the main growth factors for the internet of things is that data will come mostly from devices and not humans, although humans set the policies for gathering the data in the first place. Similarly, we can predict that computers that receive data will be enabled to make decisions based on that information, albeit under guidance and constraints. In most cases those decisions will be executed by computers who send requests for additional actions out to other devices, again mediated by human-generated policies. Driving the implementation of a billing plan, rates, discounts and commitments could well be executed by policy-driven computers too.

A universal truth in business is that all roads lead to data. In an increasingly complex and connected world the ability of an organisation to collect, manage and analyse data effectively separates the winners from the losers. This new wave of data will become the future of online advertising. However, while it is necessary to direct your marketing efforts, this increased availability of data can come at a hefty price.