Airbloc Whitepaper

In the modern digital advertising market, ‘data’ equals to a strategic choice of weapon.
Personalized advertising – which targets customers who are likely to buy the products based on
data – are often used for data monetization from IT giants such as Google, Facebook, and other
major search engines. These companies use ‘personal interests data’ to expose ads, and generate
sales.

Nonetheless, to the ‘person’ who sources ‘personal interests data’, not a single penny from
targeted ad sales is returned. Not only that, individual users do not know the manner in which
their data is collected, priced, and sold to the data consumers. Moreover, individuals do not have
the freedom to choose types of ads they want to see and the vice versa.

Some advertisers, on the other hand, abruptly changes the Terms of Use without explicit
permission from the user, or collect user data through crawling. Moreover, advertisers inevitably
share their collected data from their services with other advertising platforms and/or agencies to
boost advertisement effectiveness. In this process, user data can be passed on to an unknown
third party, travelling far beyond the specified scope of the Terms of Use, at which time the
individual’s rights may be seriously infringed.

Advertisers are dissatisfied, too. User interests data enabled improved ROI compared to the past,
but the target audience remains to be statistically ‘guessed’, based on indirectly collected data.
To execute a highly effective targeted ads with custom audiences and/or lookalike audiences,
advertisers need direct user interests data beyond simple piece of information such as gender, age,
and place of residence. As advertising cost has risen due to soaring demand within centralized
advertising platforms such Google and Facebook, how to optimize marketing and maximize ROI
have become a much demanded theme even for the advertisers.

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Airbloc Whitepaper

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