User Profile Targeted Ad Serving System
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Solution Overview
Problem
Current online search engines rely on query-driven advertisements, which are transient and unreliable indicators of user interests, leading to ineffective targeting of advertisements to users' personal interests.
Innovation Solution
An advertisement serving system that creates user profiles based on prior searches, interactions, demographics, and site associations, allowing advertisers to bid for user profiles and display targeted advertisements, ensuring that ads are shown to users with matching interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If query-driven advertisements are used, then advertisements can be displayed based on user search terms, but the targeting reliability deteriorates because queries are transient and unreliable indicators of user interests
Solution Approach 1:
The system performs preliminary actions by collecting user data (searches, interactions, demographics, site associations) over time to build comprehensive user profiles before advertisement selection. This allows the system to have user interest information ready in advance, making advertisement targeting more reliable rather than relying solely on transient queries.
Solution Approach 2:
The invention transitions from one-dimensional query-based targeting to multi-dimensional user profile-based targeting. User profiles incorporate multiple dimensions including search history, interaction patterns, demographic information, and site associations, creating a holistic view of user interests that is far more reliable than single query terms.
2Measurement precision
If user profiles are created and stored centrally, then advertisement targeting accuracy improves, but system complexity increases due to profile management infrastructure
Solution Approach 1:
The system segments the profile management functionality into distinct modular components: profile creation module, profile storage module, profile retrieval module, and profile update module. Each component handles specific tasks independently, reducing overall system complexity while maintaining high measurement precision through specialized processing at each stage.
Solution Approach 2:
The patent introduces intermediary components including profile databases that store user data, matching algorithms that bridge user profiles with advertisement criteria, and coordination layers that manage interactions between different system modules. These intermediaries simplify the overall architecture by providing clear interfaces and abstraction layers.
3Adaptability or versatility
If advertisers bid for user profiles, then advertisement relevance to user interests increases, but the system requires complex bidding and price optimization mechanisms
Solution Approach 1:
The advertisement selection system is designed to be dynamic, allowing advertisers to adjust bids in real-time based on user profile characteristics, campaign performance, and market conditions. The system continuously optimizes pricing strategies by analyzing match quality between user profiles and advertisement criteria, enabling flexible adaptation without requiring complex static pricing structures.
Solution Approach 2:
The system implements feedback mechanisms where advertisement performance data (clicks, conversions, user engagement) is continuously collected and used to refine bidding strategies. This feedback loop allows the system to automatically optimize advertisement selection and pricing based on actual user responses, reducing the need for manual complex pricing configurations.
Data Source
AI summary
Targeted advertisements are provided to an advertisement consumer based on a user profile, a page profile, or a combination thereof. In embodiment where a user of a search engine is an advertisement consumer, the user utilizes a search engine to obtain search results relevant to a search query. A user profile of the user's interests is used to select advertisements for inclusion with search results. The user profile is evaluated by an advertisement server which determines which advertiser(s) offers a highest price for the user profile. Advertisements from these advertisers are then selected. In another embodiment, where the user is accessing a page on a third party website, the page may include a request for advertisements. A page profile is evaluated by an advertisement server that determines which advertiser(s) offers a highest price for the page profile. Advertisements from these advertisers are then selected, and provided to the user, where they are included in the retrieved page.