Mobile Event Segmentation for Accurate Location-Based Targeting
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Solution Overview
Problem
Existing technologies struggle to accurately characterize mobile entities based on location data from mobile devices due to the inherent differences between traditional Internet browsing behaviors and location-based interactions, leading to inefficiencies in delivering targeted information.
Innovation Solution
A system and method for characterizing mobile entities by creating pre-defined places associated with business/brand names, processing information requests to determine if they trigger these places, and applying filters to derive behavioral segments, which are then used to annotate incoming requests, reducing computation time and improving accuracy for information providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location data of mobile devices is collected and processed to create behavioral segments, then accuracy of targeted information delivery is improved, but computation time and processing complexity increase
Solution Approach 1:
The system pre-processes and stores location data in a structured format before actual information delivery is needed. By preparing and organizing the data in advance into behavioral segments with associated characteristics, the system reduces computation time during real-time information delivery while maintaining high accuracy in targeting.
2Ease of operation
If traditional Internet browsing behavior methods are used to segment mobile users, then ease of operation is maintained, but measurement precision deteriorates due to differences in location data characteristics
Solution Approach 1:
The system adapts the segmentation approach by changing the parameters and methods used to process location data specifically. Instead of using traditional browsing behavior parameters, the system employs location-specific parameters such as geographic coordinates, movement patterns, and spatial relationships to create accurate behavioral segments that reflect mobile user characteristics.
3Measurement precision
If more location data is collected from mobile devices, then accuracy of user characterization is improved, but device complexity and data management requirements increase
Solution Approach 1:
The system segments the collected location data into organized categories and behavioral patterns. By dividing the complex data into manageable segments with specific characteristics and groupings, the system maintains high accuracy in user characterization while reducing the complexity of data management and processing through structured organization.
Data Source
AI summary
The present disclosure provides novel techniques to segment mobile entities based signals from mobile devices associated with these mobile entities. In certain embodiments, a first set of mobile entities and a second set of mobile entities are determined based at least on first and second predefined constraints. A feature set related to a mobile segment is also identified, the feature set including a plurality of features. A plurality of feature gains corresponding, respectively, to the plurality of features are then determined, and a set of mobile entities are add to the mobile segment based at least one the plurality of feature gains, and for each particular feature of the plurality of features, frequency of events associated with each of the set of mobile entities and having the particular feature.