Method, computer system, and stored program for accumulating descriptive profile data along with source information for use in targeting third-party advertisements

What is this patent about?

’249 is related to the field of digital information brokerage and the systematic aggregation of consumer data. It specifically addresses the technical and economic challenges of building comprehensive user profiles in a fragmented online environment where individual websites only see a small slice of a visitor's behavior. The invention provides a framework for multiple independent entities to contribute data to a centralized repository, creating a more complete picture of a user for applications like targeted advertising and actuarial risk assessment.

The underlying idea behind ’249 is to treat individual data points as discrete assets with trackable ownership and economic value. Instead of simply merging databases, the system acts as a clearinghouse that facilitates the exchange of specific user traits between unaffiliated parties. By maintaining a ledger of which provider contributed which specific detail, the system enables a micro-payment royalty model. This ensures that data providers are compensated whenever their specific contribution is utilized to facilitate a transaction, such as serving a highly relevant advertisement.

The claims of ’249 focus on an automated method and system for gathering profile data through URL redirection. When a user visits a third-party website, a portion of that page triggers a redirect to the central system, allowing it to receive partial profile attributes from the third party. The system then automatically appends this new data to an existing record associated with that same entity. Crucially, the claims require the generation of an electronic record that maps every specific attribute back to the original third-party contributor to manage the subsequent use of that data for targeted advertising.

In practice, the invention functions as a dynamic, multi-tenant data hub. When a visitor arrives at a participating website, the site shares what it knows—such as a cookie or a specific interest—with the central server. The server then searches its databank to find a matching profile. If the incoming data contains new information, the system updates the master profile and logs the provider's contribution. Conversely, if the central databank contains details the website lacks, the website can 'purchase' those attributes to better tailor the visitor's experience in real-time.

This approach differs from prior methods by moving away from the bulk sale of static databases and toward a fluid, attribute-level marketplace. Traditional systems often struggle with data veracity and stale information; however, this invention introduces a credibility weighting mechanism. By comparing new data against existing records and external databases, the system can mathematically adjust the reliability score of a profile. This creates a self-correcting ecosystem where the value of information is tied to its accuracy and its proven utility in the advertising market.