Mihnea Tufis, Eurecat, WP 4
Missing information about the value of data transactions is one of the barriers to establishing pricing models for data-as-commodity. We reviewed articles from online editions of tech magazines, newspapers, tech reports and identified a number of data platforms that are monetizing personal data. Table 1 summarizes our findings and presents the reward that each of these companies pays to their users in exchange for types of data they are willing to share.
|Data trader||Reward||What kind of data?|
|Datum||0.01 USD / month||Location|
|CitizenMe||0.1 GBP||Personal data and preferences via online quiz (10 questions)|
|Datacoup||8 USD / month||Social media feed;
Credit card transactions details.
|Luft Research||100 USD / month||Browser history, search history;
Fill in questionnaires;
Audio recordings via device’s microphone.
|Permission.io||Token (non-exchangeable)||Watch ads.|
|Wibson||Vouchers / points (1p = 0.02 USD)||Location (15 pts);
Facebook, LinkedIn (20 pts);
Device information (25 pts);
Google accounts (NA).
|Shawn Buckles on Kickstarter||350 USD (the whole bundle)||Everything: personal data, location, medical, train travel patterns, personal calendar, emails, social media, consumer preferences, browser history, blog entries.|
|Cambridge Analytica||0.75 USD / record||Name, gender, location;
Indicators of political views and involvement;
|Proximus||700 EUR / report||Market research report: location, movement, SIM country of origin.
*supposedly anonymized data.
|AT&T Gigabit||-29 USD / month||Visited webpages;
Interaction with links and ads.
|Telefonica||NA; supposedly full control to the user||Data bank of user activities on the network.|
Table 1: Platforms for collecting and monetizing personal data.
This synthesis allows us to draw some conclusions with respect to the practice of collecting data for transaction purposes:
The wide variety of personal data collected by data brokers: identification, demographic, location, behavioral, online activity, psychological, product and political preferences. Most of the times, this data is sold in bundles, which prompts several questions: are all these equally important to a buyer, are they equally sensitive for a seller, how do each of these stakeholders should value them?
The wide price range at which the same type of data is sold. Luft Research pays 100 USD/month for a bundle containing location, social media activity and internet activity, whereas Datacoup pays 8 USD/month for a similar package. Furthermore, location is priced as low as 0.01 USD/month by Datum and approximately 0.30 USD when acquired by Wibson.
The packaging method that best incentivizes users to sell their data. A reward as low as 1 cent/month for sharing only the location data might not be convincing a contributor to give it away; however, a bundle of several data types that can amount as high as 100 USD/month could prompt individuals to start investing time in building, managing and selling data portfolios.
Too little of these platforms are functioning in a transparent way. They sprung into existence predicating the fact that they are empowering the user to retake control and monetize their personal data, but with few exceptions (e.g., Wibson) these platforms are not making it clear, how are they treating the collected data with respect to user privacy, nor who is acquiring the data and to which purposes.
A particular area to keep an eye on is the telecom industry, which long realized its data collection potential and is now exploring ways to monetize the troves of data it collects. When Belgian telecom operator Proximus sells bundles of SIM-traces for a minimum of 700 EUR/report , this raises questions about data ownership. More disturbing practices coming from the United States, where AT&T collects and uses all online user activity of their Gigabit service via deep-packet inspection , allowing users to opt-out only by paying an additional 29 USD/month, essentially enforcing a cost on privacy.
One of the big challenges of data valuation will be to attach the right value to data, taking into account the process through which it was generated, its compliance to legal frameworks, the sensitivity to further ethical issue raised by subjects and users alike and transparency of subsequent uses.