Software Feature Utilization via Usage Log Analysis

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Software applications in organizations often have unused or underutilized features due to lack of awareness among users, leading to suboptimal productivity and delayed software updates, with existing solutions like customer support and FAQs being inefficient and not scalable.

Innovation Solution

A method and system that analyzes usage logs to identify unused features and provides tailored scenarios to users through a network interface, promoting the use of these features by recommending specific courses of action, utilizing a database of scenarios and user profiling to enhance feature utilization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If automated software updates are provided, then users are relieved from manual update checks, but users remain unaware of new features and cannot make full use of them

Engineering Contradiction:

Improveautomatic update installationVSAvoiduser awareness of new features

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The system implements feedback by analyzing user interaction data and usage patterns to identify which new features remain unused, then proactively providing targeted information and guidance about these features through the user interface, creating a closed loop that connects automated updates with user education

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system enables self-service by automatically generating personalized feature guidance based on individual user behavior patterns, eliminating the need for manual user research or generic training materials while delivering customized information about features relevant to each user's workflow

Inventive Principle:

Principle #25Self-service

2Loss of information

If users actively explore and learn new software through user manuals, then they may discover useful features, but this requires significant time and effort from users

Engineering Contradiction:

Improvefeature discoveryVSAvoidtime for reading manuals

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system performs preliminary action by pre-analyzing user behavior patterns and pre-identifying relevant unused features before the user needs to learn them, then delivering personalized guidance about specific features that match the user's actual workflow and organizational context

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system applies local quality by providing customized feature information tailored to each user's specific organizational context, role, and usage patterns rather than presenting generic feature lists, making the information locally relevant to each user's work environment

Inventive Principle:

Principle #3Local quality

3Adaptability or versatility

If extensive customer support is provided to help users understand features, then users receive personalized advice, but this requires a large number of trained representatives and is not scalable

Engineering Contradiction:

Improvepersonalized feature adviceVSAvoidcustomer service infrastructure

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system implements self-service by automatically generating personalized feature recommendations and guidance based on individual user behavior analysis, eliminating the need for human customer service representatives while delivering customized advice that adapts to each user's specific needs and context

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces the mechanical system of human customer service representatives with an automated computational system that analyzes user behavior data, identifies unused features, and delivers personalized guidance, substituting human labor with algorithmic processing while maintaining personalization

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Loss of information

If users consult databases of frequently asked questions, then they can find relevant information, but this requires users to actively search and navigate the index system which creates a barrier

Engineering Contradiction:

Improveaccess to usage informationVSAvoidaccessibility of information

Core Design Contradiction:

Loss of informationVSEase of operation

Solution Approach 1:

The system implements self-service by automatically generating and delivering personalized feature guidance based on individual user behavior patterns, eliminating the need for users to actively search databases or navigate index systems while providing relevant information directly in their workflow context

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS10552430B2Increasing utilization of a computer system

Publication Date: 2020.02.04 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

A method of increasing utilization of a computer program product having a plurality of features usable by multiple user groups. The method comprises: accessing a database storing multiple scenarios each defining a course of action characterised by usage of a respective subset of the features; via a network interface, receiving logs of past usage of some or all of these features by a target user group; based on the received logs, identifying one or more of the features that are unused or less frequently used by the target user group, and selecting one or more of the scenarios for the target entity which make use of the one or more unused or less frequently features. An indication of the one or more selected scenarios is output via a network interface, thereby causing the target entity to follow the course of action defined in at least one of the selected scenarios.