Opt-in Ad Targeting via User Data Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current online advertising systems struggle to effectively target specific consumer groups, leading to low return on investment for advertisers, as they often display ads to all website visitors regardless of demographic fit, and charge a flat fee based on website popularity rather than user data quality.
Innovation Solution
A system and method that present customized opt-in windows to users by collecting and validating user information against advertiser-defined criteria, displaying relevant ads only to matching users, and billing advertisers based on objective success metrics such as user engagement and data quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If ads are displayed to all website visitors, then ad coverage is maximized, but ad relevance to specific consumer groups deteriorates
Solution Approach 1:
The patent segments the audience by collecting demographic and behavioral data from users, then divides ad delivery into targeted groups based on predefined criteria. Instead of showing all ads to everyone, the system segments users and matches specific ads to specific segments, thereby maintaining high coverage while improving relevance.
Solution Approach 2:
The patent applies local quality by tailoring ad content to specific user groups based on their characteristics. Different portions of the advertising system serve different functions for different user segments - generic ads for broad audiences, targeted ads for specific demographics - thereby optimizing relevance locally for each group while maintaining overall system coverage.
2Ease of manufacture
If a flat fee is charged based on website popularity, then billing simplicity is maintained, but billing accuracy reflecting user data quality deteriorates
Solution Approach 1:
The patent changes the billing parameter from a simple flat fee based on website traffic to a multi-factor pricing model that incorporates user data quality metrics, opt-in rates, and demographic matching accuracy. This allows billing to reflect the actual value provided to advertisers while maintaining a structured calculation framework.
Solution Approach 2:
The patent implements feedback mechanisms where billing rates are adjusted based on performance data. Advertisers pay based on actual results such as opt-in conversions and demographic matching success, creating a feedback loop where billing accuracy improves over time based on measured outcomes rather than relying solely on preliminary website popularity metrics.
3Measurement precision
If user information is collected and validated against multiple sources, then user data quality is improved, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-establishing validation rules and criteria before user data collection. Multiple data sources and validation algorithms are pre-configured and tested, so that when user information is collected, the validation process automatically executes according to predetermined parameters. This reduces operational complexity during actual data processing while maintaining high data quality standards.
4Productivity
If opt-in windows are customized based on user matching, then ad effectiveness is improved, but processing time increases
Solution Approach 1:
The patent uses preliminary action by pre-segmenting users into demographic groups and pre-matching ads to these segments before the opt-in window is displayed. User data is collected and categorized in advance, and relevant ads are pre-selected based on matching algorithms. When the opt-in window appears, the customization process is already largely complete, significantly reducing display processing time while maintaining high ad effectiveness.
Data Source
AI summary
In a system and method for flexibly offering on-line promotions to visitors of a website hosted by a server, when a user signs up with the website, the server collects a plurality of user data from the visitor. If a user's data matches predetermined criteria from an advertiser, then online promotions from this advertiser are included in an opt-in window displayed to the user. In some aspects, a bifurcated client/server scripting approach isolates personally identifiable information until or unless a user opts-into an offer or offers. The server dynamically generates pricing information for each advertiser according to a flexible algorithm. The flexible algorithm depends on the type and quality of user requested by the advertiser.