Adaptive Consumer Location Data Collection for Analytics
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Solution Overview
Problem
Conventional methods for determining consumer characteristics, such as direct questioning, often provide inaccurate or incomplete information due to human error and are costly and time-consuming, while existing automated collection methods may not fully leverage the potential of consumer location data for comprehensive analytics.
Innovation Solution
A method involving programmed processors to collect and analyze consumer location data at adjustable intervals, using wireless networks to obtain location information from portable devices, and comparing it to known settings to infer consumer behaviors, preferences, and identities, thereby producing accurate and reliable consumer analytics without requiring direct consumer interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location data is collected continuously at short intervals, then measurement precision and reliability of consumer analytics improve, but device power consumption increases and data collection cost increases
Solution Approach 1:
The patent applies dynamics by making the data collection interval adaptive rather than fixed. The system dynamically adjusts the time interval between location data collections based on the consumer's current location context. When a consumer is at a known setting (home, work, frequent locations), the system extends the interval to conserve power. When the consumer is at an unknown or potentially interesting location, the system shortens the interval to capture behavior data. This dynamic adjustment resolves the contradiction between measurement precision and power consumption.
Solution Approach 2:
The system changes the parameter of time interval between location data collections based on the consumer's location context. By comparing current location against known settings and adjusting the sampling interval parameter accordingly, the system optimizes the balance between data accuracy and power consumption. This parameter change allows the system to collect sufficient data for accurate analytics while minimizing unnecessary power usage during periods when continuous monitoring is not critical.
2Loss of information
If location data is collected at frequent intervals, then completeness of consumer behavior data improves, but device power consumption and operational cost increase
Solution Approach 1:
The system dynamically adjusts the data collection frequency based on contextual need. Rather than using a static frequent sampling rate, the system modifies the sampling interval in real-time based on whether the consumer is at a known or unknown location. This ensures complete capture of behavior data at critical moments while avoiding redundant collections at predictable locations, thus maintaining information completeness while reducing energy loss.
Solution Approach 2:
The system applies partial action by collecting location data at selective intervals rather than continuously. It uses the minimum necessary sampling frequency to capture meaningful consumer behavior patterns by focusing data collection on transitions to unknown locations or significant events, rather than uniformly frequent sampling. This partial action approach maintains data completeness for behavioral analysis while significantly reducing power consumption compared to continuous or uniformly frequent collection.
3Measurement precision
If direct questioning methods are used to collect consumer information, then data collection cost and time increase, but measurement precision may be compromised due to human error
Solution Approach 1:
The patent replaces the mechanical system of direct human questioning (surveys, interviews, questionnaires) with an automated electronic system that passively collects location data from portable devices. This substitution eliminates human error in self-reporting and removes the time burden of completing surveys. The automated system continuously and accurately tracks consumer locations without requiring consumer time or effort, while providing objective behavioral data that is more reliable than self-reported information.
4Duration of action of moving object
If data collection interval is extended to conserve power, then device battery life improves, but measurement precision and data completeness deteriorate
Solution Approach 1:
The system uses dynamic interval adjustment to extend battery life without sacrificing measurement precision. By making the sampling interval adaptive based on location context, the system extends intervals during periods when continuous monitoring is less critical (at known settings) while maintaining shorter intervals when behavior capture is important (at unknown or significant locations). This dynamic approach ensures adequate battery life while preserving the accuracy needed for meaningful consumer analytics.
Solution Approach 2:
The system changes the time interval parameter based on the consumer's location context to optimize the balance between battery life and measurement precision. When the consumer is at predictable locations (home, work, frequent venues), the system increases the interval to extend battery life. When the consumer visits new or potentially significant locations, the system decreases the interval to maintain data accuracy. This parameter change strategy resolves the contradiction between duration and precision.
Data Source
AI summary
In embodiments, methods and systems for electronically capturing consumer location data for consumer behavior analysis may be provided. The location data may be gathered for one or more consumers from any suitable source. In some cases, the location data may be gathered using electronic devices associated with consumers, such as mobile phones. The gathered data may be analyzed to determine behavior patterns or other characteristics of the one or more consumers. Further, inferences or predictions about consumers may be derived based on the characteristics. The inferences and predictions may be the basis of consumer analytics supplied to a business or other entity.