Anonymous User Profile Brokering for Mobile Ad Targeting
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Solution Overview
Problem
Current mobile advertising technologies lack the ability to effectively personalize advertisements due to the siloed nature of mobile data, with insufficient techniques to correlate and analyze user information for real-time targeting, and existing methods are not suitable for mobile devices as they rely on cookies and IP addresses which are unreliable on mobile networks.
Innovation Solution
A brokering platform that collects and correlates mobile subscriber data across various dimensions to create enriched user profiles, allowing for secure sharing of anonymous user information with content servers and advertisement servers for targeted advertising without compromising user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If user data is collected and stored in silos across mobile network, then data availability for personalization increases, but data correlation capability remains insufficient
Solution Approach 1:
The patent merges previously siloed user data from multiple sources (network data, device data, application data) into a unified user profile structure. The brokering platform consolidates these disparate data sources and correlates them using device identifiers to create comprehensive anonymous user profiles, thereby improving data availability while providing the correlation capability that was previously insufficient.
Solution Approach 2:
The brokering platform acts as an intermediary between data sources and content servers/ad servers. It receives data from multiple sources, processes and correlates it into anonymous user profiles, and then provides this correlated data to requesting servers. This intermediary structure enables data correlation without requiring complex integration between all data sources and all consumers.
2Ease of operation
If traditional cookie-based targeting methods are used, then advertising personalization is achieved, but reliability decreases on mobile networks
Solution Approach 1:
The patent creates anonymous user profiles that are copies of user behavior and characteristics data, stored in a brokering platform. These profile copies can be retrieved and used for targeting without requiring the original device state or cookies. The system uses device identifiers to create and retrieve these profile copies, providing reliable personalized advertising that doesn't depend on the fragility of cookies or IP addresses.
3Productivity
If detailed user information is shared with third parties, then ad effectiveness improves, but user privacy protection is compromised
Solution Approach 1:
The patent extracts personally identifiable information (PII) from user data and replaces it with anonymous device identifiers. The system creates and maintains anonymous user profiles that contain behavioral and demographic data useful for advertising, but deliberately exclude direct identifiers. This extraction of PII allows detailed user information to be shared for advertising purposes while protecting user privacy through anonymization.
Solution Approach 2:
The patent transforms user data by changing its parameters from identifiable to anonymous. Device identifiers are used as keys to access profile data, but the actual profile data contains no direct personal identifiers. The system changes the parameter of user identification from named entities to anonymous tokens, enabling effective advertising while maintaining privacy protection.
Data Source
AI summary
The invention provides a system and method for sharing anonymous user profiles with a third party. In one aspect of the invention, the system shares user profiles with content servers on a mobile data network so that they may select content responsive to the user's profile. The system provides a store of user profiles for associating profile information with either a source IP address or mobile phone number, where the profile includes information on the user and the user's network usage. The system detects a user's transaction request and inspects it for either an IP address or phone number, which it uses to retrieve the appropriate profile. The system subsequently applies predetermined opt-out policies to determine how much of the user profile may be provided in response to the profile request. The system then returns the profile information such that the user's identity is masked.