Targeted Advertising System Using Data Segmentation and Privacy Protection
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Solution Overview
Problem
Merchants face challenges in effectively managing their advertising budgets due to high costs of national advertising and the need for targeted advertisements that respect consumer privacy, as existing methods fail to provide a complete picture of subscriber purchasing behavior and compromise privacy.
Innovation Solution
A system and method that calculates the potential customer base by aggregating transaction and viewership data to identify optimal time slots and channels for targeted advertising, using hashed references to maintain privacy, and adjusts advertising based on sales data to optimize ROI.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If national advertising is used to reach potential customers, then advertisement coverage is improved, but advertising cost increases
Solution Approach 1:
The patent segments the national advertising market into localized geographical areas (zip codes, counties, states) and targets advertisements only to regions where potential customers are concentrated. This segmentation allows merchants to reduce advertising spend by eliminating waste in areas with low potential customer density while maintaining effective coverage in high-potential regions.
Solution Approach 2:
The patent applies local quality by delivering customized advertisements tailored to specific geographical locations and local customer characteristics. Advertisements are adapted to reflect regional preferences, demographics, and purchasing behaviors, making them more effective in each local market while reducing the need for broad national spending.
2Productivity
If subscriber data is collected to enable targeted advertising, then advertisement effectiveness is improved, but consumer privacy is compromised
Solution Approach 1:
The patent introduces an intermediary layer that processes and aggregates subscriber data without exposing individual personally identifiable information. The system uses hashed references and aggregated metrics to identify potential customers and their viewing patterns, enabling targeted advertising while maintaining a barrier between raw personal data and advertising delivery mechanisms.
Solution Approach 2:
The patent creates anonymized copies of subscriber data that retain useful patterns for targeting (such as viewing habits and demographic characteristics) while removing or hashing personally identifiable information. These copied datasets enable effective targeted advertising without compromising the privacy of individual subscribers.
3Quantity of substance
If advertisement spending is increased to reach more customers, then potential customer reach is improved, but ROI decreases due to budget constraints
Solution Approach 1:
The patent performs preliminary analysis of subscriber data to identify potential customers and their preferred viewing patterns before advertisements are delivered. By pre-segmenting the audience and predicting which subscribers are most likely to convert, the system maximizes the impact of every advertising dollar spent, reaching more effective potential customers without increasing overall budget.
Solution Approach 2:
The patent implements feedback loops that continuously monitor advertisement performance and sales data to refine targeting strategies. The system learns from actual customer responses and adjusts future advertising allocations to focus on high-performing segments, improving ROI while expanding reach to new potential customers.
Data Source
AI summary
A system and method for broadcasting an advertisement of a product in a network is disclosed. The system includes a first interface unit for receiving transaction data of large number of customers from a financial service provider system, a second interface unit for receiving a viewership data from a network service provider system, a configuration database which stores a master rule, first and second sets of rules and a processing unit. The method includes (i) receiving the transaction data, (ii) processing the transaction data based on the first set of rule to obtain a potential customer base, (iii) receiving the viewership data, (iv) mapping the viewership data with the potential customer base to obtain an user database, (v) processing and aggregating the user database to obtain an optimal user database, and (vi) broadcasting the advertisement through the network service provider system in accordance to a second set of rule.