Targeted Content Delivery via Consumer Spending Analysis
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Solution Overview
Problem
Current online advertising methods are costly and yield limited results, as they often employ a shotgun approach with expensive keyword purchases and lack the ability to effectively target consumers who are ready, able, and willing to purchase products or services.
Innovation Solution
A personalized consumer advertising system that identifies consumers based on their actual financial expenditures, allowing marketers to create custom profiles for specific consumers within a market, geographical location, or income bracket, and presents targeted advertisements to those who match the desired profile.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If advertisers use broad-spectrum online advertising campaigns to reach masses of consumers, then the quantity of consumers exposed to advertisements increases, but the cost per consumer increases and the return on investment decreases
Solution Approach 1:
The patent segments the consumer base into distinct groups based on financial institution type (commercial banks vs. credit unions) and spending patterns. This allows advertisers to target specific segments with tailored campaigns rather than using broad-spectrum advertising, thereby reducing wasted spend on uninterested consumers while maintaining reach to relevant audiences.
Solution Approach 2:
The system performs preliminary actions by pre-screening and identifying consumers who are 'ready, able, and willing' to purchase before advertisements are delivered. Financial institutions and the advertising system analyze consumer spending patterns, account balances, and purchase histories in advance to create targeted lists of qualified consumers, ensuring advertising spend is focused only on high-probability prospects.
2Loss of information
If advertisers purchase expensive keywords for search engine placement, then advertisement visibility increases, but the cost per click increases and the ability to identify purchase-ready consumers decreases
Solution Approach 1:
The system implements feedback loops where consumer responses to advertisements (clicks, conversions, purchases) are tracked and fed back into the screening process. This allows the system to learn from actual consumer behavior and refine targeting criteria, improving the identification of purchase-ready consumers over time while optimizing advertising spend based on measured performance.
Solution Approach 2:
The patent replaces the mechanical keyword-purchasing system with an automated digital screening and matching system. Instead of manually selecting and purchasing keywords, the system uses algorithms to automatically analyze consumer data, identify qualified prospects, and deliver targeted advertisements, thereby reducing reliance on expensive keyword auctions while improving consumer intent identification.
3Measurement precision
If advertisers use behavioral targeting based on website visits, then the precision of consumer profiling increases, but the ability to identify consumers with actual purchasing power decreases
Solution Approach 1:
The patent merges two previously separate approaches: behavioral targeting (website visit tracking) and financial capability assessment (spending pattern analysis). By combining data from both consumer behavior monitoring and financial institution spending records, the system creates a comprehensive profile that identifies consumers who are not only interested in products but also have the actual purchasing power to buy, thereby resolving the contradiction between behavior tracking precision and financial capability identification.
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.