I'm working on a blockchain solution that gives consumers the ability to control and monetize their data:
www.databook.one
@dasil003 I agree that Facebook's ARPU is super low. However, with that statistic is related to ad revenue, not revenue from the sale of data. Facebook doesn't publically sell its consumer data. Thus, we're talking apples and oranges.
To buy raw data, you need to go to data brokers, who are currently earning $250 billion per year from selling consumer data. Raw data is super valuable because you can build predictive models with it. With very small samples of customer data, powerful models can be built that can deliver millions or even hundreds of millions of dollars to a business' bottom line.
I can testify to this because I led the technology team for company that earned millions by leveraging machine learning to predict who would sell their house bellow market prices in the next few months.
The problem with buying data from data brokers is that the quality is awful. For example, the accuracy rate of America's largest data broker, Acxiom is only 50%. This problem is holding back the advancement of machine learning. If consumers linked and verified their own data, we could improve that accuracy rate significantly and deliver much more accurate models to businesses.
Thus, we expect that compensation paid by companies to individuals sharing their complete data profiles could be significant.
I've seen estimates that the value of data will reach $7,500K per American per year by 2022.
Even if we reached 10% of this estimate, I'd want that money in my pocket instead of some data broker.
What are your thoughts?
www.databook.one
@dasil003 I agree that Facebook's ARPU is super low. However, with that statistic is related to ad revenue, not revenue from the sale of data. Facebook doesn't publically sell its consumer data. Thus, we're talking apples and oranges.
To buy raw data, you need to go to data brokers, who are currently earning $250 billion per year from selling consumer data. Raw data is super valuable because you can build predictive models with it. With very small samples of customer data, powerful models can be built that can deliver millions or even hundreds of millions of dollars to a business' bottom line.
I can testify to this because I led the technology team for company that earned millions by leveraging machine learning to predict who would sell their house bellow market prices in the next few months.
The problem with buying data from data brokers is that the quality is awful. For example, the accuracy rate of America's largest data broker, Acxiom is only 50%. This problem is holding back the advancement of machine learning. If consumers linked and verified their own data, we could improve that accuracy rate significantly and deliver much more accurate models to businesses.
Thus, we expect that compensation paid by companies to individuals sharing their complete data profiles could be significant.
I've seen estimates that the value of data will reach $7,500K per American per year by 2022.
Even if we reached 10% of this estimate, I'd want that money in my pocket instead of some data broker.
What are your thoughts?