Smart Contract Data Monetization for Privacy-Controlled Ad Targeting
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Solution Overview
Problem
Current advertising methods rely heavily on blind or semi-blind targeting, resulting in irrelevant advertisements that fail to account for users' future intentions, with only a small percentage of Internet users driving clicks and a significant portion of advertisements going unseen.
Innovation Solution
A system utilizing smart contracts to manage and monetize user data by creating blockchain tokens based on user data sets, allowing users to control and be compensated for their data, and enabling targeted advertisements aligned with their interests and holdings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional blind advertising or cookie-based targeting is used, then advertising coverage is broad, but advertising relevance to users is poor
Solution Approach 1:
The patent segments user data into specific categories (holdings, interests, demographics) and uses this segmented information to create targeted advertising groups. Instead of treating all users uniformly, the system divides the user base into segments based on their data profiles, allowing advertisers to target specific segments with relevant ads while maintaining broad overall coverage.
Solution Approach 2:
The patent applies local quality by tailoring advertising content to match the specific characteristics of different user segments. Each user receives advertising based on their local data profile (holdings, interests, demographics) rather than a uniform approach, thereby improving relevance while maintaining broad coverage across diverse user groups.
2Measurement precision
If user data is collected and used for targeting, then advertising relevance improves, but user privacy control is reduced
Solution Approach 1:
The patent implements self-service by allowing users to actively manage their own data profiles through the platform. Users can control what data is shared, with whom, and for what purposes. This empowers users to maintain privacy control while still enabling targeted advertising, as they selectively share data rather than having it collected without consent.
Solution Approach 2:
The patent introduces a platform intermediary that mediates between users and advertisers. This intermediary manages data collection, storage, and sharing according to user preferences, and facilitates targeted advertising without requiring direct user-advertiser data sharing. The platform acts as a trusted mediator that protects user privacy while enabling relevant advertising.
3Quantity of substance
If comprehensive user data is collected from multiple sources, then data completeness improves, but data security risks increase
Solution Approach 1:
The patent segments user data into different categories and stores them in a structured manner within the platform. By organizing data into segments (holdings, interests, demographics) and implementing segmented access controls, the system maintains data completeness while reducing security risks through localized access management rather than centralized vulnerable storage.
Solution Approach 2:
The platform acts as an intermediary that securely manages comprehensive user data from multiple sources. It implements security protocols, encryption, and access controls to protect the complete data set while enabling authorized access for targeted advertising. The intermediary structure isolates raw data from direct exposure, reducing security risks despite data completeness.
Data Source
AI summary
A system, method, device, and platform for monetizing data. A smart contract is established indicating how data from a user is retrieved and utilized by a data platform. Data associated with a user is automatically retrieved from one of a number of sources based on the smart contract. The data is added to a data set associated with the user. One or more blockchain tokens are created based on the data set of the user. The user is compensated for monetizing the one or more blockchain tokens associated with the data set of the user.