Consumer Analytics System Visit Detection Adjustment
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Solution Overview
Problem
Current methods for collecting consumer data often rely on direct questioning, which can be inaccurate and time-consuming, failing to capture timely and relevant information about consumer behaviors and preferences, especially when these behaviors are linked to location data.
Innovation Solution
A consumer analytics system that utilizes location data to infer and predict consumer behaviors by detecting visits to specific settings, allowing for real-time data collection and analysis, and adjusting its processes based on this data to improve accuracy and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct questioning methods are used to collect consumer data, then information can be obtained from consumers, but the data is inaccurate and time-consuming
Solution Approach 1:
The patent replaces direct questioning (mechanical data collection method) with automated location-based detection systems using mobile devices and GPS technology. This substitution eliminates the need for time-consuming surveys and interviews while providing more accurate, objective data about actual consumer behaviors and movements.
Solution Approach 2:
The patent introduces location data from mobile devices as an intermediary to indirectly capture consumer behavior information. Instead of directly asking consumers about their behaviors, the system uses location data as a mediator to infer and detect actual behaviors, preferences, and patterns automatically.
2Reliability
If location data is used to detect consumer visits, then timely and relevant data can be collected, but the system complexity increases
Solution Approach 1:
The patent leverages the universal nature of mobile devices that consumers already carry, which have built-in location capabilities. By utilizing this existing multi-functional device, the system avoids creating separate specialized equipment, thereby reducing overall system complexity while maintaining high data reliability and timeliness.
Solution Approach 2:
The system employs automated self-service mechanisms where mobile devices automatically track and report location data without requiring consumer intervention. The visit detection process operates autonomously, automatically comparing location data against known settings to identify visits, thereby reducing system complexity through automation rather than manual processes.
3Measurement precision
If visit detection processes are adjusted based on consumer input, then detection accuracy improves, but processing complexity increases
Solution Approach 1:
The patent implements feedback loops where consumer inputs (such as correcting misidentified visits or providing additional information) are used to continuously refine and adjust the visit detection algorithms. This feedback mechanism improves detection accuracy over time while the automated nature of the adjustment process prevents excessive complexity from accumulating in the system.
Data Source
AI summary
A method and system for adjusting a process for identifying settings visited by a consumer based at least in part on electronically-derived consumer location data. A method and system are provided for gathering location data for consumers and identifying points of interest (POIs) visited by the consumers based on the location data. Based on a comparison of settings identified by a process to settings that are identified in data collected from external data sources, the system may determine whether to adjust the visit detection process. The system may adjust the visit detection process by adjusting a way in which settings are defined in a data set, by adding or removing settings from a data set, and/or by changing a manner in which the visit detection process determines whether a location corresponds to a setting in the data set.