Panel Application Capturing Search Suggestions Across Web Pages
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Solution Overview
Problem
Current systems lack an effective method to collect and analyze user search suggestions across multiple web pages to understand consumer behavior and changes in interest over time, particularly in relation to product offerings.
Innovation Solution
A system comprising client devices with web browsers and a panel application that captures and sends search suggestion data to a server, which correlates character sequences with lists of phrases, ranks intended phrases, and generates reports on consumer interest changes over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If search suggestions are collected from multiple web pages across client devices, then the comprehensiveness of consumer behavior data is improved, but the system complexity increases
Solution Approach 1:
A panel application acts as an intermediary component installed on client devices that intercepts and captures search suggestion data from multiple web pages. This intermediary layer collects character sequences and corresponding search suggestions without requiring changes to the web pages themselves, thereby improving data comprehensiveness while managing system complexity through a dedicated collection module.
Solution Approach 2:
The system is designed to collect search suggestion data from multiple different web pages across various client devices simultaneously. The panel application universally captures search suggestions regardless of the specific web page or client device, enabling comprehensive consumer behavior data collection across diverse platforms and sources.
2Loss of information
If search suggestion data is collected and analyzed across multiple web pages, then insights into consumer interest changes are improved, but the data processing complexity increases
Solution Approach 1:
The system processes collected search suggestion data to generate feedback in the form of consumer interest change reports. By analyzing patterns in character sequences and search suggestions across multiple web pages, the system provides actionable insights about evolving consumer preferences and product offerings, transforming raw data into meaningful feedback for stakeholders.
Solution Approach 2:
The data processing system segments search suggestion data by character sequences and groups corresponding phrases into ranked lists. This segmentation approach organizes the complex multi-source data into structured, analyzable units that can be processed efficiently and used to generate consumer interest reports.
3Measurement precision
If character sequences and search suggestions are correlated into ranked lists, then the precision of consumer intent analysis is improved, but the computational requirements increase
Solution Approach 1:
The system changes parameters by ranking phrases based on their likelihood of representing intended consumer intent. By transforming raw search suggestion data into ranked lists where phrases are ordered by probability of being the user's intended search, the system improves measurement precision of consumer intent while managing computational requirements through efficient ranking algorithms.
Data Source
AI summary
A system includes a plurality of client devices and a server system. Each of the client devices is configured to implement at least one web browser and a panel application. The web browser is configured to access a plurality of different web pages that each provide search capability and are each configured to display search suggestions in response to character sequences entered by a user when using the search capability. The panel application is configured to send indications of displayed search suggestions and corresponding character sequences to a server system. The server system is configured to generate, based on the received indications, a data structure that correlates character sequences to lists of phrases.