Online Research System Integrating Behavioral Data
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Solution Overview
Problem
Current market research faces challenges such as inadequate dataset scale and scope, lack of data structure, siloed data, and insufficient individual consent for research use, which limits the effectiveness and utility of research findings.
Innovation Solution
A system and method for researching online behavior using a digital community with opt-in members who contribute data through the SavvyConnect software, integrating various data sources, and providing ownership to contributors, ensuring informed consent and secure data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional market research methods are used, then research can be conducted with existing data, but the dataset scale and scope are inadequate and data is siloed
Solution Approach 1:
The patent merges multiple data sources including web browsing data, mobile app usage data, social media data, and survey responses into a single integrated research platform. This consolidation enables access to large-scale, diverse datasets while providing unified analysis capabilities, directly addressing the inadequate dataset scale and siloed data problems.
Solution Approach 2:
The research platform is designed as a universal system that can collect, store, and analyze multiple types of data from various sources through a single interface. This multi-functional approach allows the system to handle diverse data formats and sources without requiring separate specialized systems, thereby increasing dataset scale while managing integration complexity.
2Measurement precision
If comprehensive data collection is implemented, then research insights are enhanced, but privacy and security concerns arise
Solution Approach 1:
The patent introduces data aggregation and anonymization as intermediary processes between raw data collection and research analysis. These intermediaries transform personal data into aggregated statistical data, maintaining research insights quality while eliminating direct access to individual privacy-sensitive information, thus reducing privacy and security risks.
Solution Approach 2:
The system changes the state of data from individual-level detailed information to aggregated statistical representations. By transforming data parameters from granular personal data to summarized metrics, the system maintains measurement precision for research insights while mitigating privacy and security concerns associated with raw personal data.
3Adaptability or versatility
If data is aggregated from multiple sources, then research scope increases, but data structure and organization become complex
Solution Approach 1:
The patent segments the complex data structure into standardized categories and types (e.g., demographic data, behavioral data, transactional data). This segmentation organizes diverse data from multiple sources into manageable, consistent structures, enabling expanded research scope while reducing the complexity of data organization and management.
Solution Approach 2:
The system applies standardized data formats and parameter definitions to transform and organize data from various sources. By changing the representation parameters of data into uniform structures, the system achieves versatile research capabilities across multiple data types while simplifying the underlying data organization complexity.
4Reliability
If individual consent is obtained for data use, then research ethics are improved, but participation and data collection are limited
Solution Approach 1:
The patent uses data aggregation and anonymization as intermediaries that allow research to proceed with aggregated data rather than requiring direct individual consent for each data point. This intermediary approach maintains research ethics by ensuring data is collected and used responsibly, while enabling larger data collection volumes through aggregated statistical data that represents multiple individuals without requiring separate consents for each record.
Data Source
AI summary
An online behavior, survey, and social research system is provided. In some embodiments, the system comprises a hardware processor; and a non-transitory machine-readable storage medium encoded with instructions executable by the hardware processor to perform a method comprising: collecting data from a user device of a user, the data representing actions performed by the user on one or more network sites; receiving an event match configuration specifying one or more patterns of interest; generating event matches based on the collected data and the event match configuration, wherein each of the event matches represents a portion of the collected data matching with one or more of the patterns of interest; receiving a project configuration specifying a time period of interest; generating a user journey report comprising the event matches occurring during the time period of interest; and providing the user journey report to a client device.