Visitor Engagement Scoring Framework for Retroactive Website Assessment
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Solution Overview
Problem
Existing systems lack the ability to dynamically assess and retroactively update visitor engagement scores for websites, requiring significant processing power, data storage, and data processing techniques to accurately reflect dynamic changes in user interactions.
Innovation Solution
A framework that allows website owners to customize scoring frameworks by selecting events and assigning score values, enabling real-time and retroactive scoring of visitor engagement, using a computing system to track and analyze user interactions and update historic scores accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a computing system tracks and processes all user interaction data to accurately assess visitor engagement, then measurement precision is improved, but device complexity and data storage requirements increase
Solution Approach 1:
The patent segments visitor engagement assessment into discrete event types (clicks, scrolls, form submissions, video plays) with assigned weights. This segmentation allows the system to process specific interaction categories independently rather than analyzing all raw data continuously, reducing computational complexity while maintaining measurement precision through targeted event tracking.
Solution Approach 2:
The system transforms raw interaction data into standardized engagement scores by applying parameter changes - assigning numerical weights to different event types and aggregating them into a composite metric. This parameter transformation simplifies the data structure from diverse interaction types to a unified score, reducing device complexity while preserving engagement assessment accuracy.
2Adaptability or versatility
If the scoring framework is updated dynamically to reflect changing website priorities, then adaptability is improved, but processing power and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-defining event types and their associated weights in a configurable framework before actual visitor interactions occur. When the framework needs updating, only the weight parameters need modification rather than reprocessing historical data, enabling adaptability with minimal computational overhead.
Solution Approach 2:
The scoring framework is designed to be dynamic and configurable, allowing website owners to adjust event weights and priorities without system reconfiguration. This dynamic structure enables the framework to adapt to changing website goals while maintaining efficient processing through a stable underlying computational model.
3Measurement precision
If retroactive updating of historical engagement scores is implemented when framework changes occur, then measurement precision is improved, but loss of time and processing overhead increase
Solution Approach 1:
The system extracts only the necessary historical data elements (event occurrences and timestamps) needed for recalculation when the framework changes, rather than reprocessing complete historical datasets. This selective extraction minimizes the time and resources required for retroactive score updates while maintaining precision in the recalculated metrics.
4Measurement precision
If comprehensive tracking of all user actions is implemented, then measurement precision is improved, but loss of information and data storage requirements worsen
Solution Approach 1:
The system extracts and stores only the essential engagement events and their associated metadata in a structured format, filtering out redundant or irrelevant interaction data. This selective data extraction maintains measurement precision by capturing all necessary engagement indicators while significantly reducing the volume of stored information compared to comprehensive raw data retention.
Data Source
AI summary
Disclosed are techniques for designating a scoring framework for scoring a website based on visitor engagement. A method can include: receiving tracking data recorded at a client-side computing device when a user at the client-side computing device performs actions, during a session, in a website associated with a website owner, identifying events in the tracking data, transmitting the identified events for presentation in a graphical user interface (GUI) display at a computing device of the website owner, receiving input indicating selection of a subset of the identified events to be tracked and a score value assignment for each event in the subset, designating a scoring framework based on the received input, the scoring framework being automatically applied to tracking data from sessions with the website that are associated with client-side computing devices to determine visitor engagement scores for the website, and storing the scoring framework in association with the website.