Geographic-Demographic Consumption Indices Grid for Ad Targeting
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Solution Overview
Problem
Existing advertising methods often fail to effectively target advertisements to individuals based on their geographic and demographic characteristics, leading to irrelevant advertising and reduced effectiveness.
Innovation Solution
The use of a geographic-demographic consumption indices grid to identify consumption indices and affinity levels for products, allowing for targeted advertising by correlating geographic locations, demographic information, and online media interests to deliver relevant advertisements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If traditional advertising methods are used to reach broad audiences, then advertising coverage is improved, but advertising relevance deteriorates
Solution Approach 1:
The patent segments the advertising approach by dividing the broad audience into specific geographic and demographic segments. It creates a grid system that breaks down geographic areas into manageable units and cross-references them with demographic characteristics, allowing advertisers to target specific segments rather than broadcasting to everyone uniformly.
Solution Approach 2:
The patent applies local quality by tailoring advertising content to specific geographic locations and demographic groups. Instead of using uniform advertising messages everywhere, the system adjusts advertising relevance to match local characteristics, ensuring that each segment receives advertising appropriate to its specific needs and preferences.
2Loss of information
If advertising is targeted to specific individuals, then advertising relevance is improved, but data processing complexity deteriorates
Solution Approach 1:
The patent reduces data processing complexity by segmenting the population into predefined geographic and demographic categories rather than analyzing individual data points. The grid system pre-organizes data into manageable segments, making it easier to process and analyze aggregated information at the segment level rather than at the individual level.
Solution Approach 2:
The patent introduces a new dimensional approach by creating a multi-dimensional grid that combines geographic dimensions with demographic dimensions. This dimensional framework transforms complex individual-level data into structured segment-level data, simplifying the analysis and targeting process while maintaining high relevance.
3Quantity of substance
If broad advertising campaigns are used, then advertising reach is improved, but advertising efficiency deteriorates
Solution Approach 1:
The patent maintains advertising reach by covering multiple geographic segments and demographic groups through the grid system, while improving efficiency by concentrating resources on segments most likely to respond. Rather than uniformly distributing advertising across all populations, the system identifies and prioritizes high-value segments.
Solution Approach 2:
The patent changes the parameters of advertising deployment by using the geographic-demographic grid to dynamically adjust targeting parameters. This allows the system to optimize advertising efficiency by modifying which segments are targeted and with what intensity, based on the structured data from the grid analysis.
Data Source
AI summary
A disclosed example method involves generating a geographic-based consumption index for a product based on a first per-person sales volume of the product in a first cell of a plurality of geographic cells of a larger geographic area. The example method also involves generating a demographic-based consumption index for the product based on a second per-person sales volume of the product for a demographic group in the first cell. An advertisement to present to a person is selected based on an online web interest, a geographic location, and a demographic of the person and further based on the geographic-based consumption index and the demographic-based consumption index.