Insight Delivery Using User Command Vocabulary Tracking
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Solution Overview
Problem
Existing systems fail to accurately determine the proficiency of users with software and provide insights at the right time and cadence, leading to inefficient user skill development and high churn rates.
Innovation Solution
A system that measures user proficiency through unique command execution counts, compares it to ideal user vocabularies, and autonomously delivers insights based on historical data and expert analysis to guide users towards becoming proficient subscribers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If session count is used as the trigger to control insight delivery, then the system can track total usage time, but the granularity is insufficient and variability amongst users is extreme, resulting in mediocre correlation to desired outcome
Solution Approach 1:
The patent changes the measurement parameter from session count (coarse-grained) to vocabulary count of unique commands (fine-grained). This parameter change enables precise measurement of user proficiency by tracking the diversity of commands executed, directly resolving the contradiction between measurement precision and system complexity.
Solution Approach 2:
The patent replaces the mechanical counting system (session count) with an information-based system (vocabulary analysis of command usage). This substitution allows for more nuanced measurement of user proficiency by analyzing the semantic content of user interactions rather than merely counting time-based metrics.
2Productivity
If insights are provided too frequently, then user learning may be accelerated, but user overload and frustration occur; if provided too infrequently, then proficiency development slows
Solution Approach 1:
The patent implements feedback by continuously monitoring user command usage patterns and adjusting insight delivery based on measured proficiency growth. The system provides insights at rates proportional to demonstrated learning, preventing overload while maintaining accelerated development for users who can handle more information.
Solution Approach 2:
The patent makes the insight delivery rate dynamic rather than static. The system adjusts the frequency and timing of insights based on real-time measurement of user proficiency through vocabulary tracking, allowing the delivery rate to adapt to each user's learning capacity and pace.
3Ease of operation
If insights are customized to individual user proficiency levels, then learning effectiveness improves, but system complexity and computational requirements increase
Solution Approach 1:
The patent implements self-service by having the system automatically measure user proficiency through vocabulary tracking and autonomously curate and deliver appropriate insights without requiring manual intervention. This automation reduces the operational complexity of providing personalized learning support.
Solution Approach 2:
The patent introduces vocabulary count as an intermediary metric that bridges raw user interactions and personalized insight delivery. This intermediary simplifies the complexity by providing a single measurable indicator of proficiency that drives the entire customization process.
4Measurement precision
If the system tracks detailed command usage to measure proficiency, then insight accuracy improves, but data processing requirements and system resources increase
Solution Approach 1:
The patent extracts only the essential information needed for proficiency measurement - the vocabulary of unique commands executed - while discarding redundant data. This extraction approach maintains measurement precision by focusing on the distinctive set of commands rather than processing all user interactions in detail.
Solution Approach 2:
The patent discards redundant command repetition data while recovering and retaining the essential vocabulary information. By tracking only unique commands rather than all command instances, the system maintains accurate proficiency measurement with reduced data processing requirements.
Data Source
AI summary
A computer-implemented method and system provide for insights/recommendations to a user of a software product. A computer application autonomously determines a count of distinct commands executed by a user. Based on the count, the computer application autonomously determines the insight that includes a feature or new distinct command. The computer application then autonomously recommends the insight to the user.