Product-Query Graph Interface for eCommerce Campaign Analysis
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Solution Overview
Problem
Current eCommerce platforms lack effective methods for evaluating user buying trends and advertising campaign effectiveness, necessitating improved tools for analyzing product-query relationships and advertising performance.
Innovation Solution
A graphical user interface (GUI) featuring an interactive Product-Query Graph is introduced, allowing users to input queries or product identifiers, displaying relevant products and user queries with predictive purchase relationships, along with associated statistics and advertising performance indicators, facilitating better trend analysis and campaign evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional eCommerce platforms use standard analytics methods, then implementation is simple, but the ability to evaluate user buying trends and advertising effectiveness is insufficient
Solution Approach 1:
The patent introduces a Product-Query Graph as an intermediary data structure that mediates between raw user interaction data and analytical insights. The graph captures relationships between products and user queries, enabling precise evaluation of buying trends and advertising effectiveness without requiring complex analytical algorithms. This intermediary representation simplifies the analysis while improving measurement precision.
Solution Approach 2:
The patent replaces traditional mechanical analytics systems with a knowledge graph-based approach. Instead of using complex statistical models and machine learning algorithms, the system uses graph-based relationship mapping to analyze user behavior patterns, product associations, and advertising performance, achieving high measurement precision with simpler system architecture.
2Loss of information
If eCommerce platforms implement comprehensive user behavior tracking, then buying trend evaluation improves, but data processing complexity increases
Solution Approach 1:
The patent segments user behavior data into discrete product-query relationships and represents them as edges in a graph structure. Each interaction is broken down into specific nodes (products, queries) and relationships (viewed, purchased, advertised), enabling comprehensive information capture while simplifying data processing through modular graph operations.
Solution Approach 2:
The patent creates a graph-based copy or representation of user behavior data rather than processing raw interaction logs directly. The Product-Query Graph serves as an abstracted copy that preserves all necessary information about user interactions while enabling efficient querying and analysis through graph traversal algorithms.
3Difficulty of detecting and measuring
If visual analytics tools are added to the platform, then user behavior analysis capability improves, but interface complexity increases
Solution Approach 1:
The patent implements self-service visual analytics where the system automatically generates and updates the Product-Query Graph based on incoming user interaction data. The graph visually represents buying trends, product associations, and advertising effectiveness without requiring manual configuration or complex interface interactions, maintaining ease of operation while enhancing analysis capability.
Data Source
AI summary
A computer-implemented process includes receiving with an eCommerce platform from a user over a network a first product-search keyword, generating to a display of the user a graphical user interface (GUI) including a first selectable icon showing the first keyword, a first selectable image of a first product and a first connector between the first icon and first image, the first connector indicating that the first product was previously purchased using the eCommerce platform in response to the platform receiving the first keyword, and in response to user selection of the icon, generating to the GUI a set of performance indicators characterizing an advertising campaign associated with at least one of the first keyword and first product within the eCommerce platform.