Multi-source Consumer Behavior Tracking via Weighted Attribute Pairing
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Solution Overview
Problem
Current web analytics systems struggle to track consumer behavior across multiple visits using various devices and channels without clear identification, leading to missed information or incorrect data combination.
Innovation Solution
A process for associating unattributed information from multiple cybernetic sources with consumers by creating a master registration, detecting matching characteristics, and attributing records with confidence levels, which allows for tracking consumer behavior across disparate devices and channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cookie record identifiers are used to track consumer behavior, then consumer activity can be tracked across visits, but tracking fails when consumer deletes cookies or uses different devices
Solution Approach 1:
The patent introduces an intermediary identification system that uses device characteristics, browser information, and behavioral patterns as mediators to link consumer activities across different devices and sessions. This intermediary layer replaces direct cookie-based identification, allowing tracking to persist even when cookies are deleted or devices change.
Solution Approach 2:
The system changes the parameters used for identification from static cookie identifiers to dynamic combinations of device characteristics, browser information, and behavioral patterns. By monitoring changes in these parameters over time, the system can identify returning consumers without relying on persistent cookies.
2Measurement precision
If clear identification such as registration number is required for each device use, then data accuracy improves, but information collection becomes incomplete without such identification
Solution Approach 1:
Instead of requiring complete registration information for every device use, the system collects partial identification data (device characteristics, browser information) and progressively builds a more complete consumer profile over multiple interactions. This allows the system to track and analyze consumer behavior even when full identification is not available at each touchpoint.
Solution Approach 2:
The system performs preliminary data collection using available device and browser information before complete consumer identification is established. By accumulating partial data points across multiple visits, the system can later match and consolidate consumer activities even without initial clear identification.
3Adaptability or versatility
If multiple consumers use the same device with a single cookie, then device sharing is accommodated, but consumer-specific tracking becomes inaccurate
Solution Approach 1:
The patent segments the identification process into multiple independent data dimensions (device characteristics, browser information, behavioral patterns) rather than relying on a single shared cookie. This segmentation allows the system to differentiate between multiple consumers using the same device by analyzing variations in their individual patterns across these segmented dimensions.
Data Source
AI summary
A process for tracking a consumer's behavior based on his or her entries into a number of cybernetic device sources such as personal computers, automated goods and services dispensing kiosks, automated teller machines and cell phones does not depend exclusively upon the presence of cookies implanted into such devices by vendors or upon a consumer's having provided a positive identification form. The process uses a pairing algorithm to comb elements of information from the source device visitation records in search of one or more common characteristics that can be presumptively attributed to a single consumer. Characteristics such as source device identifiers, phone numbers, street addresses or email addresses are each weighted by a weighting factor that is used to identify the consumer and attribute the visitation record and its associated activity to that consumer at a calculated confidence level. The attributed information can analyzed to track that consumer's behavior.