Recently, Comcast reached a $33 million settlement over claims that it published personal information of more than 75,000 customers — even though those customers had specifically paid a fee for their information to be kept private. As a consequence, the company will pay $100 compensation to each victim.
This settlement is a turning point in our technological history. Not just because it involves the biggest cable company in the world, but, more importantly, because the clients who suffered the breach had specifically paid for their data to be protected.
This case is particularly interesting because, for the first time, it puts a price tag on the amount victims should receive when their personal information is illegally published.
Beyond this mere example, the issue of the value of personal data is key to our economy. Data has become the most important strategic asset of pure players like Google and Facebook. And among the biggest companies in the world, by market capitalization, a majority see their valuation estimated as a function of their user base and the data they collect.
A first approach could be to analyze the issue of valuation of personal data through the eyes of the shareholder. In other words, personal data is worth whatever the shareholder is willing to pay to acquire client data from a data-centric company, as was the case when, WhatsApp and Instagram were acquired by Facebook.
At the time of acquisition, these companies are often not profitable and are generally being valuated on the basis of their user base and data. It is not uncommon to hear that these acquisitions are aimed at buying the user base. However, one cannot buy an individual or a particular relationship. In the knowledge economy, it is the data about that individual that is being acquired and, in particular, an ability to maintain the quality and strength of that relationship over time.
In light of this valuation method, Facebook decided to acquire WhatsApp for $19 billion; that is, to pay $30 for each of its 600 million users. Similarly, the company headquartered in Menlo Park also paid $30 for each of the 33 million Instagram users back in 2012. A similar computation was applied when Minecraft was acquired by Microsoft.
Data has become a strategic asset that allows companies to acquire or maintain a competitive edge. In this situation, the value of a user varies from about $15 to more than $40. The difference lies mostly in the potential expected from each user. This potential depends on the company’s business and, therefore, on the type of data it collects. In the world of big data, the richer and wider the information the company has, the more money it can make from its users’ activity, and the bigger the company’s valuation. The valuation of a company, of its clients and of the data it owns are therefore intertwined.
A second way to approach this question is to account for the revenues generated by the customers (when they do. It was not the case for Instagram or Whatsapp at the time of their acquisitions.) The generally accepted valuation method in this situation is to estimate the value of a client as a function of the net present value it will generate for the company in the future. This is called the Customer Lifetime Value (CLV).
The CLV is predicted by using customers’ transaction data and allows decision makers to undertake the most relevant and profitable business actions. The CLV estimates the value of the commercial relationship the company has with individual customers. Hence it provides a maximalist range of our personal data valuation. The personal data collected by a company and its relationship with individual customers are therefore intertwined.
Finally, how do we, as users of products and services of digital companies, value our own personal data? It is interesting to note that while many fiercely oppose corporations using their personal data, very few are willing to pay an extra fee to protect it.
Indeed, many services offering to protect our data have emerged on the web. And unlike companies like Google or Facebook that monetize our data via their advertising services, those alternatives are often fee-based for obvious economic reasons. For instance, FastMail offers an alternative to Gmail. Or Zoho, which is a Google Docs-like offer. But these services have not really been successful until now. The dominant model remains one of free access to services in exchange for a commercial use of our data. This market tendency to monetize data collected on the Internet is accelerating.
Source: Cyber Security Intelligence