Non-transactional Data Capture via Device Fingerprinting
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Solution Overview
Problem
Online retailers face challenges in capturing and utilizing non-transactional user interactions data effectively, leading to wasted opportunities for targeted marketing, as existing methods often alienate users or are too costly for print communications.
Innovation Solution
A system utilizing the OneTag library to track and analyze user interactions across multiple pages, enabling identification and statistical evaluation of users without intrusive methods, thereby creating an engagement score for targeted marketing efforts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If online presences use heavy-handed approaches like email distributions to every customer or forced login requirements, then data capture capability is improved, but user experience deteriorates and users may be alienated
Solution Approach 1:
The patent introduces an intermediary system that uses device fingerprints and probabilistic matching to identify users without forcing login. This intermediary layer captures non-transactional data while maintaining user anonymity, thus preventing user alienation while improving data capture capability.
Solution Approach 2:
The patent replaces the mechanical system of forced login and explicit user identification with a computational approach using device fingerprinting and probabilistic matching. This substitution allows passive data collection without user intervention, improving data capture while avoiding user alienation.
2Quantity of substance
If online presences send print communications to broadly targeted audiences, then marketing reach is improved, but marketing cost increases significantly
Solution Approach 1:
The patent applies local quality by segmenting the audience based on captured non-transactional data and engagement metrics. Instead of uniform broad distribution, communications are targeted to specific local segments with high conversion probability, reducing overall marketing cost while maintaining effective reach.
Solution Approach 2:
The patent changes the parameter of audience selection from broad and uniform to segmented and probability-based. By using engagement scores and behavioral data to adjust targeting parameters, the system achieves cost-effective marketing with optimized reach to receptive audiences.
3Loss of information
If users are forced to log in to capture non-transactional data, then data association capability is improved, but user experience deteriorates
Solution Approach 1:
The patent implements self-service by automatically capturing device fingerprints and identifying users without requiring any user action. The system serves itself by passively collecting identification data through normal browsing behavior, eliminating the need for forced login while maintaining visitor identification capability.
Data Source
AI summary
As a client device accesses and interacts with a web server of an online retailer, an engagement evaluation server gathers data from both the client device and the web server. Over time, as the client device is used to access the web server and other web servers within the evaluation server network, a profile is built and maintained that describes some aspects of the client device interaction with the web server, including recency of visits, frequency of visits, frequency of views of products, frequency of shopping cart creation and modification, and other factors indicative of the user being engaged with the online retailer. The evaluation server performs statistical analysis and data modeling on profiles in order to generate an engagement score, and then provides the contact information for profiles meeting certain criteria.