Continuous Consumer Behavior Tracking System for E-Commerce Analytics
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Solution Overview
Problem
Conventional consumer behavior modeling in e-commerce struggles to measure transaction volumes consistently and reliably, particularly in evaluating the impact of Transaction Related Offerings (TROs) on buyer behavior, as it relies on incomplete and disconnected data such as click-streams that end at payment, limiting the ability to track consumer behavior across multiple online environments.
Innovation Solution
The development of methodologies, systems, and software that perform continuous analytics throughout the consumer's online journey, from surfing to post-purchase, to measure consumer-to-customer conversion and determine the efficacy of TROs by combining TRO implemented tracking, seller reporting, and cookie or shared object technology, allowing for the collection of comprehensive consumer behavior data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional click-stream tracking is used to measure consumer behavior, then implementation is simple and cost-effective, but the measurement is incomplete and disconnected as click-streams end at payment
Solution Approach 1:
The patent merges multiple data sources including click-stream data, cookie data, shared object data, seller reporting data, and third-party provider data into a unified consumer behavior tracking system. This integration allows continuous tracking from pre-purchase through post-purchase activities across multiple online environments, resolving the limitation of conventional click-stream tracking that ends at payment.
Solution Approach 2:
The tracking system is designed to be universal by implementing multiple tracking mechanisms (cookies, shared objects, seller reporting interfaces) that can track consumer behavior across different websites, sellers, and transaction stages. This multi-functional approach enables the system to capture comprehensive consumer behavior data beyond what a single tracking method could achieve.
2Adaptability or versatility
If data is collected only within a single online environment, then tracking is straightforward, but the ability to track consumer behavior across multiple online environments is limited
Solution Approach 1:
The system implements universal tracking capabilities using cookies and shared objects that can be recognized across multiple online environments. These tracking mechanisms allow the system to follow consumers across different websites and sellers, maintaining continuous tracking capability and preventing loss of consumer behavior information across environment boundaries.
Solution Approach 2:
The patent introduces intermediary components including third-party providers and centralized data aggregation systems that mediate between multiple online environments and the tracking system. These intermediaries facilitate cross-environment data collection by bridging gaps between different online platforms and consolidating consumer behavior data from multiple sources.
3Reliability
If transaction volume is measured using conventional methods, then measurement is simple, but the measurement is not verifiable, consistent, reliable or scalable
Solution Approach 1:
The patent combines multiple independent data sources including click-stream data, cookie data, seller reporting data, and third-party provider data to measure transaction volume. This multi-source verification approach enhances reliability by cross-validating transaction measurements across different data streams, making the measurement more verifiable and consistent while maintaining scalability.
4Measurement precision
If click-stream data alone is used for consumer behavior modeling, then data collection is simple, but the predictive accuracy for consumer responses to TROs is insufficient
Solution Approach 1:
The system merges multiple data sources including pre-purchase click-stream data, post-purchase transaction data, consumer response data to TROs, and demographic information from third-party providers. This comprehensive data integration significantly increases the quantity and quality of consumer behavior data available for modeling, thereby improving predictive accuracy for consumer responses to Transaction Related Offerings.
Data Source
AI summary
Methodologies, systems, components and software are provided that perform web analytics to measure visitor to consumer conversion continuously throughout surfing, through conversion and past completion of a purchase on-line. In accordance with at least one embodiment, such methodologies, systems, components and software may be utilized to determine efficacy of a plurality of parameters relating to one or more Transaction Related Offerings (TROs). In accordance with at least one embodiment of the invention, such methodologies, systems, components and software may be utilized to configure one or more Consumer Behavior Decision Models (CBDMs) and/or generate consumer behavior data.