Predictive Demographics Inference from App Usage
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Solution Overview
Problem
Current methods for understanding user demographics and behavior in the context of mobile apps are inaccurate and inefficient, particularly due to respondent subjectivity in surveys and the complexity of tracking app usage across multiple devices.
Innovation Solution
A method and system for predicting user demographics and preferences using deterministic user data from app usage statistics, employing predictive models that estimate demographic characteristics and purchase intent, which can be applied to provide personalized digital content and improve marketing campaigns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional user survey type studies or interviews are used to collect demographic data, then data collection is simple to implement, but the accuracy and reliability of demographic information deteriorates due to respondent subjectivity and inaccuracy
Solution Approach 1:
The patent replaces the mechanical system of manual surveys and interviews with an automated electronic metering system that collects app usage data. This substitution eliminates respondent subjectivity while maintaining ease of data collection, as the automated system objectively measures actual app usage patterns to infer demographic characteristics.
Solution Approach 2:
The patent introduces an intermediary element - the app usage metering system - that indirectly measures demographic characteristics through observable app usage behavior rather than directly asking users about their demographics. This intermediary approach maintains simplicity while improving accuracy by using objective behavioral data.
2Measurement precision
If automated metering software is deployed across multiple electronic terminal devices to track app usage, then measurement accuracy and objectivity improve, but device complexity and implementation difficulty increase
Solution Approach 1:
The patent applies universality by designing a metering system that functions across multiple types of electronic terminal devices (smartphones, tablets, laptops, smart TVs) using the same core technology. This multi-functional approach improves measurement accuracy across devices while avoiding the need for device-specific complex implementations.
Solution Approach 2:
The patent segments the complex task of multi-device tracking into manageable components: individual device metering, data collection, and centralized processing. This segmentation allows each component to be simpler while the overall system achieves high measurement precision across multiple devices.
3Measurement precision
If comprehensive app usage data is collected from all installed applications to predict demographics, then prediction accuracy improves, but data processing complexity and computational requirements increase
Solution Approach 1:
The patent extracts only the most relevant features from comprehensive app usage data for demographic prediction, rather than processing all available data. This extraction approach maintains high prediction accuracy by focusing on key indicators while reducing computational complexity and processing requirements.
Solution Approach 2:
The patent applies partial action by collecting and processing a subset of app usage data that is sufficient for accurate demographic prediction without requiring analysis of all installed applications. This partial approach achieves the necessary prediction accuracy while avoiding excessive computational complexity.
Data Source
AI summary
Electronic arrangement comprising a data interface for transferring data with external elements, at least one processor for processing instructions and other data, and memory for storing the instructions and other data, said at least one processor being configured, in accordance with the stored instructions, to obtain at least one predictive user model including one or more demographic characteristics as dependent variables to be predicted and usage statistics of applications as explanatory variables, obtain deterministic usage statistics indicative of digital applications a target user has utilized during a monitoring period, and determine, through utilization of the deterministic usage statistics obtained during the monitoring period as input to the at least one established predictive model, an estimate of said one or more of the demographic characteristics of the target user.