User Segmentation via Fingerprint Scoring for Cost-Based Deployment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional user segmentation methods in enterprises are often heuristic and rely on predefined characteristics, leading to incorrect segmentation and high deployment costs, as they do not accurately reflect the diverse IT needs of users and lack cost optimization for IT infrastructure deployment.
Innovation Solution
A method for automated user segmentation based on user fingerprint scores that quantify enterprise-level needs and deployment fingerprint scores that quantify solution capabilities, allowing for the identification of optimal user segments and deployment solutions, while also addressing outlier users and segments to optimize costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional heuristic user segmentation methods are used, then user segmentation can be performed with simple predefined characteristics, but the segmentation accuracy deteriorates and deployment costs increase
Solution Approach 1:
The patent transforms user segmentation from qualitative heuristic categorization to quantitative fingerprint-based scoring. User fingerprints and deployment fingerprints convert user characteristics and deployment solution capabilities into numerical score sets, enabling precise matching through parameter comparison rather than simple category assignment.
Solution Approach 2:
The patent replaces manual heuristic segmentation mechanics with an automated computational system. The fingerprint-based approach uses algorithmic scoring and matching to substitute human expert judgment, achieving consistent and accurate segmentation without manual intervention.
2Loss of time
If conventional user segmentation methods are used, then deployment can proceed with minimal analysis, but deployment costs increase due to incorrect segmentation
Solution Approach 1:
The patent performs user segmentation and fingerprint matching before deployment decision-making. By pre-calculating user fingerprints, deployment fingerprints, and compatibility scores, the system enables informed deployment choices that avoid costly rework from incorrect segmentation.
Solution Approach 2:
The patent implements a feedback mechanism where deployment decisions are based on quantitative compatibility scores between user fingerprints and deployment fingerprints. This feedback loop ensures that deployment choices are optimized for both accuracy and cost-effectiveness.
3Reliability
If user segmentation is performed without cost optimization, then all user needs can be addressed comprehensively, but deployment costs increase
Solution Approach 1:
The patent applies different levels of deployment solutions to different user segments based on their specific needs. Rather than uniform comprehensive deployment, the system matches deployment capabilities locally to each segment's fingerprint profile, optimizing resource allocation.
Solution Approach 2:
The patent uses fingerprint score thresholds and compatibility parameters to determine optimal segmentation numbers. By adjusting these parameters, the system balances comprehensive user needs coverage against deployment cost constraints.
Data Source
AI summary
Described herein, is a method for user segmentation for cost-based deployment of enterprise infrastructure. According to an implementation, for each of the users, a user fingerprint (UFP) score set comprising rating scores that quantify levels of enterprise-level needs of the each user is determined. For each of deployment solutions of the enterprise, a deployment fingerprint (DFP) score set comprising rating scores that quantify levels of capabilities of the each deployment solution enabled to meet enterprise-level needs of the users is determined. The users are grouped into user segments based on the UFP score sets of the users. A definition of each of the user segments is determined. The definition is indicative of a user whose enterprise-level needs define characteristics of the corresponding user segment. A number of user segments is found based on a cost associated with the deployment solutions for the user segments.