Personalized Consumer Advertising Through Anonymous Spending Profiles
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Solution Overview
Problem
Current advertising methods are costly and inefficient, failing to effectively target consumers who are 'ready, able, and willing' to purchase products or services, and lack the ability to track financial transactions outside existing customer databases.
Innovation Solution
A personalized consumer advertising system that utilizes consumer financial transaction data to create targeted advertisements by associating anonymous consumer profiles with market segments, allowing advertisers to deliver ads to consumers based on their spending habits across multiple financial institutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If advertisers use traditional mass-market advertising campaigns to reach consumers, then they can reach a large number of consumers, but the cost is very high and the return is minimal (single digit conversion rate)
Solution Approach 1:
The patent segments the consumer market into distinct groups based on financial transaction data, spending patterns, and demographic information. Instead of treating all consumers uniformly, the system divides them into targeted segments that can be reached with customized advertising messages, thereby improving advertising efficiency while reducing costs.
Solution Approach 2:
The system changes the parameters used for target selection from broad demographic categories to specific financial behavior parameters such as spending patterns, transaction frequency, and account balance. This allows advertisers to target consumers based on actual purchasing behavior rather than general market assumptions.
2Measurement precision
If advertisers purchase search engine keywords to target consumers, then they can reach consumers interested in specific topics, but the cost per click is high ($5-10) and they cannot determine if the consumer is ready to purchase
Solution Approach 1:
The system incorporates feedback loops that track consumer responses to advertisements and update targeting algorithms accordingly. By monitoring which consumers convert to purchases and which do not, the system continuously refines its targeting criteria based on actual purchase behavior rather than just search intent, improving both accuracy and cost efficiency.
Solution Approach 2:
The system performs preliminary analysis of consumer financial data and spending patterns before advertising campaigns are launched. This pre-screening identifies consumers who are most likely to be ready to purchase, allowing advertisers to target only those high-probability prospects rather than casting a wide net.
3Reliability
If retailers profile customers based on their own internal data only, then they can maintain existing customers effectively, but they cannot secure additional customers from competitors
Solution Approach 1:
The patent creates a universal advertising platform that serves multiple functions: it helps retailers retain existing customers through personalized promotions while simultaneously enabling them to acquire new customers from competitors. The system aggregates financial data across multiple institutions, providing a comprehensive view that supports both retention and acquisition objectives.
Solution Approach 2:
The system acts as an intermediary between financial institutions and advertisers, bridging the gap between internal retailer data and external marketing capabilities. By partnering with financial institutions that have access to broader consumer financial data, retailers can extend their targeting capabilities beyond their own customer databases.
4Measurement precision
If the system mines detailed financial transaction data to create personalized advertisements, then advertising targeting becomes highly accurate, but consumer privacy and anonymity must be protected
Solution Approach 1:
The system extracts only the necessary information elements needed for advertising targeting from complete financial records. Instead of storing or processing full transaction details, it extracts aggregated spending patterns, category preferences, and demographic indicators, thereby maintaining targeting accuracy while minimizing privacy exposure.
Solution Approach 2:
The system creates anonymized copies of consumer profiles that contain targeting information without personally identifiable details. These synthetic profiles can be used for advertising decisions without exposing actual consumer identities, allowing accurate targeting while preserving anonymity.
Data Source
AI summary
The subject personalized consumer advertising/ad placement system provides the ability for advertisers, ad agencies, and any other applicable organization to determine and electronically present their “ideal” consumer profile and have their advertisement/promotion placed in front of all consumers who match the profile based on the anonymous mining of the consumers actual spending across a broad base of spending categories.