Targeted Ad Delivery via Financial Data Segmentation
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Solution Overview
Problem
Current online advertising methods are costly and inefficient, as they often employ a 'shotgun approach' with high costs per click and limited returns, failing to effectively target consumers who are 'ready, able, and willing' to purchase products, and lack the ability to track consumer spending outside of existing customer bases.
Innovation Solution
A personalized consumer advertising system that identifies consumers based on their actual financial expenditures, allowing for targeted ad placement by matching desired consumer profiles with financial transaction data, enabling advertisers to reach consumers who are likely to be interested in their products, while maintaining consumer anonymity and offering scalable pricing structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If advertisers use traditional broad-spectrum advertising methods to reach masses of consumers, then the reach and visibility of advertisements is improved, but the cost increases significantly and the return on investment decreases to single digits
Solution Approach 1:
The patent segments the broad consumer market into specific target groups based on financial transaction data, demographic information, and purchasing behavior. Instead of advertising to all consumers, the system divides the market and delivers ads only to relevant segments, thereby maintaining broad reach potential while improving cost efficiency by excluding non-target audiences.
Solution Approach 2:
The patent applies local quality by tailoring advertising content to specific local markets and consumer groups. The system delivers customized advertisements to different geographic regions and consumer segments based on their unique characteristics derived from financial data, rather than using a uniform advertising approach across all markets.
2Measurement precision
If advertisers use keyword-based search engine advertising, then the targeting precision is improved, but the cost per click increases to $5.00-$10.00 and the ability to identify RAW consumers is lost
Solution Approach 1:
The patent performs preliminary action by pre-screening and identifying consumers who are Ready, Able, and Willing to purchase before advertisements are delivered. The system uses financial transaction data and demographic information to pre-qualify potential customers, so that when ads are delivered, they reach only pre-identified high-probability buyers, improving both accuracy and cost efficiency.
Solution Approach 2:
The patent introduces an intermediary layer between the advertiser and the consumer - a data processing system that analyzes financial transaction data, demographic information, and purchasing behavior to identify target consumers. This intermediary filters and qualifies leads before they are presented to advertisers, reducing the cost per click by eliminating low-probability prospects.
3Loss of information
If behavioral targeting is used based on website monitoring, then the ability to target interested consumers is improved, but the system cannot identify consumers' actual purchasing power and affordability
Solution Approach 1:
The patent merges multiple data sources including financial transaction data, demographic information, website behavior data, and purchasing history into a unified consumer profile. By combining these diverse information streams, the system achieves both comprehensive interest tracking and accurate purchasing power assessment, overcoming the limitations of using any single data source alone.
Solution Approach 2:
The patent creates a universal data processing system that handles multiple types of consumer information (financial transactions, demographics, web behavior, purchasing patterns) through a single integrated platform. This multi-functional system can assess both consumer interest and purchasing power simultaneously, making it applicable to various advertising scenarios and consumer segments.
Data Source
AI summary
When incentivizing vendors to give greater discounts on items or services offered or advertised to specific customers on a third-party website in exchange for reduced advertisement pricing, a vendor enters offer parameters (e.g., item or service for sale, price or discount amount, terms of the offer, a permitted number of acceptances of the offer, etc.) into a user interface along with target customer criteria (e.g., age, gender, minimum income, etc.). The target criteria is matched to customer profile data, and an advertisement generated using the offer parameter information is presented to customers whose profiles match the target criteria. In return for offering larger discounts, a cost per event (CPE) associated with the advertisement is reduced for the vendor. An invoice is generated and transmitted to the vendor, and upon receipt of payment, the advertisement provider remits a portion of the received payment to the website owner.