Targeted Advertising System Using Consumer Lifestyle Classification
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Solution Overview
Problem
Current Internet advertising technologies, such as behavioral profiling, are limited in targeting consumers accurately due to lack of data on individual spending habits and purchasing trends across multiple retailers, leading to ineffective ad delivery.
Innovation Solution
A system and method for creating customized advertising campaigns that utilize anonymous consumer data, including bank transaction information and demographic data, to classify consumers into lifestyle groups, enabling targeted content delivery based on their purchasing habits and interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If behavioral profiling is used to target advertising based on website visits, then advertising relevance is improved, but accuracy is worsened due to lack of spending habit data
Solution Approach 1:
The patent combines multiple data sources including website visit data, purchase history data, and demographic data into a unified consumer profile. This integration allows the system to leverage both behavioral information (website visits) and financial information (spending habits) to create more accurate and relevant advertising targets, resolving the contradiction between relevance and precision.
Solution Approach 2:
The patent introduces a financial institution as an intermediary that provides purchase history and spending habit data. This intermediary bridges the gap between advertisers who need accurate spending information and consumers whose financial data is held by banks, enabling precise targeting without direct access to sensitive financial records.
2Quantity of substance
If website tracking is used to monitor user habits, then behavioral data is accumulated, but spending habit information is lost
Solution Approach 1:
The patent creates a multi-functional data collection system that serves multiple purposes: it tracks website visits for behavioral analysis, collects purchase history for spending pattern recognition, and aggregates demographic information. This universal approach allows a single system to accumulate diverse data types simultaneously, preventing the loss of spending habit information while maintaining behavioral data collection.
3Measurement precision
If individual retailer tracking is implemented, then purchasing habits are monitored, but cross-retailer data is lost
Solution Approach 1:
The patent merges data from multiple retailers and financial institutions into a unified consumer profile. By combining individual retailer tracking data with broader financial transaction data, the system achieves both precise purchasing habit monitoring and cross-retailer versatility, allowing accurate targeting regardless of which specific retailers the consumer visits.
Data Source
AI summary
A method for creating a customized advertising campaign includes displaying a list of available products and/or services for an advertising campaign, determining a list of consumers to be targeted by the advertising campaign, and selecting a product or service for the advertising campaign. The method further includes inputting advertising campaign detail information wherein the advertising campaign detail information includes at least one of an advertising campaign name, a start date, and an end date. The method also includes providing a list of one or more pre-associated banner templates for the advertising campaign, selecting one or more pre-associated banner templates for the advertising campaign, editing text of the one or more selected pre-associated banner templates, and publishing the one or more selected pre-associated banner templates according to the campaign detail information to one or more delivery websites.