Webpage Feature Engagement Tracking via Segmented Visit Detection
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Solution Overview
Problem
Current methods for providing feedback on webpages lack the ability to associate user engagement data with specific portions of the webpage, making it difficult for marketers to understand which features drive user interactions, and often require multiple user interface options that consume valuable real estate, especially on mobile devices.
Innovation Solution
A method that detects user visits to specific portions of a webpage, uses natural language processing to determine keywords indicating features, and associates user engagement inputs (like 'share', 'like', 'comment', 'rating') with those features, while providing only one user interface option for feedback per type, generating reports that highlight engagement with specific features and not others.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple user interface options are provided for feedback on different portions of the webpage, then user engagement data can be associated with specific features, but the real estate consumed on the webpage increases
Solution Approach 1:
The webpage is segmented into multiple portions, each associated with specific features or content elements. The system tracks user visits to these segmented portions and attributes engagement data to the corresponding features, enabling precise measurement without requiring separate UI options for each segment.
Solution Approach 2:
An intermediary tracking mechanism is introduced between the user and the feedback collection system. This intermediary detects user visits to specific portions and automatically associates engagement data with the appropriate features, eliminating the need for multiple dedicated UI options while maintaining measurement precision.
2Ease of manufacture
If feedback is linked to entire webpage, then implementation is simple, but the marketer cannot relate feedback to various portions of the webpage
Solution Approach 1:
The feedback measurement system is segmented from the webpage level to the feature level. By tracking user visits to specific portions and associating engagement data with those portions, the system maintains implementation simplicity while recovering lost feature-level information.
Solution Approach 2:
The system performs preliminary tracking of user visits to specific portions before collecting engagement data. This preliminary action establishes the connection between users and specific features, enabling detailed feedback analysis without complicating the overall implementation.
3Quantity of substance
If user engagement input is associated with multiple features, then comprehensive feedback is provided, but the system complexity increases
Solution Approach 1:
The system automatically associates engagement data with features based on tracked user visits. This self-service mechanism eliminates the need for manual configuration or complex processing, providing comprehensive feedback while maintaining system simplicity through automated feature attribution.
Data Source
AI summary
A method for associating user engagement data with various features of a product associated with a webpage is provided. The method includes detecting a visit to a portion of the webpage by a user. The webpage includes features of the product. A feature from the portion of the webpage is then determined using keyword of the feature. The portion includes the keyword of the feature. A user engagement input is then received for entire webpage from the first user. The webpage includes only one user interface option to provide the user engagement input of a particular type, at an instance, for entire webpage. The user engagement input is associated with the feature and not associated with other features on the webpage. A report indicating association of the user engagement input with the feature and non-association of the user engagement input with other features on the webpage is then generated.