IP Zone Targeting for Contextual Ad Relevance
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Solution Overview
Problem
Current online advertising systems lack a systemic and quantifiable linkage between user attributes and the media on which ads are displayed, limiting the relevance and efficiency of audience targeting, especially in the display, video, and mobile segments.
Innovation Solution
The integration of IP Zone Targeting with predictive modeling and real-time bidding platforms to link demographic and psychographic profiles of users with contextual relevance of web pages, using categorical ontologies and metadata scoring to optimize ad delivery based on location, demographics, and timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cookie-based audience targeting is used to identify users across publisher websites, then audience reach and targeting scale are improved, but there is no quantifiable linkage between user attributes and the contextual relevance of the media on which ads appear
Solution Approach 1:
The patent introduces IP zones as an intermediary layer that connects user attributes (derived from IP addresses) with media context (web page categories). This mediator enables quantifiable linkage by matching user profiles against media zone characteristics, thereby resolving the information gap between targeting data and contextual relevance without requiring direct access to personal user data.
Solution Approach 2:
The patent replaces the traditional cookie-based tracking mechanism with an IP zone-based system. This substitution eliminates the need for browser cookies while maintaining audience targeting capabilities through a different technical approach that focuses on geographic and demographic aggregation rather than individual user tracking.
2Measurement precision
If IP Zone Targeting is used to link user attributes with advertiser products, then audience qualification is improved, but there is no linkage between the IP Zone Audience and the context of the page that the ad will appear on
Solution Approach 1:
The patent merges IP zone audience data with media zone contextual data by creating overlapping geographic and demographic zones. This combination allows the system to simultaneously consider both user attributes and page context when determining ad relevance, thereby linking qualified audiences with appropriate media contexts through the intersection of these two zoning systems.
Solution Approach 2:
The patent applies local quality by creating granular IP zones and media zones that are geographically and demographically specific. Rather than using broad targeting categories, the system divides the market into localized zones with distinct characteristics, allowing for precise matching of user attributes with contextual relevance at a granular level.
3Productivity
If centralized data exchange platforms are used to pool user data, then audience targeting infrastructure is improved, but transparency to advertisers regarding cookie-based targeting processes is reduced
Solution Approach 1:
The patent enables advertisers to independently define their own target audiences by specifying geographic regions, demographic criteria, and media contexts without relying on pre-packaged cookie-based segments from data exchanges. This self-service approach gives advertisers direct control over targeting parameters and full transparency into how their audiences are defined and reached.
Data Source
AI summary
The system links Internet web page context with audience usage and location data to support advertising efficiency and effectiveness. An ontology of categories is created where domains and website pages are classified and scored against the links on those pages and the meta-tag key word pools that are harvested from those web pages. An ontology of high level categories are derived from the frequency of the key words appearing within the domain URL addresses of the pages, the domain of the links on those pages or within the content of the pages themselves. A method includes building a training set of web pages from a plurality of ad networks and sites where the system captures impressions in the form of real-time bids as well as click through events that include the IP address, the domain, the time of day and day of week, ad size and position, browser type, and bid amount whereby the training set is aggregated in a database whereby successful bids can be used in combination with audience and category attributes to model and score impression bids that combine the optimal mix of audience attributes, location, categorical affinity and bid price.