Customer Management System Real-Time Satisfaction Scoring
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Solution Overview
Problem
Existing customer satisfaction measurement techniques, such as customer surveys, NPS, and end-user interaction surveys, provide aggregated and lagging indicators of customer satisfaction, failing to offer real-time, individualized insights into customer sentiment and likelihood of repeat business or recommendations.
Innovation Solution
A customer management system that receives requests for current end-user status, determines associated topics, retrieves penalties for those topics, calculates a satisfaction score using a scoring equation, compares the score to predefined ranges to determine a status, and displays the current status to end-users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional customer surveys and NPS are used to measure customer satisfaction, then aggregated satisfaction levels can be obtained, but real-time individualized customer sentiment and likelihood of repeat business cannot be determined
Solution Approach 1:
The patent segments customer satisfaction measurement from aggregated levels to individual customer levels. Each customer receives a unique satisfaction score based on their specific interactions, topics, and behaviors. The system divides the customer base into individual units for analysis, enabling personalized sentiment tracking while maintaining overall aggregated insights.
Solution Approach 2:
The system implements continuous feedback loops by monitoring customer interactions in real-time and immediately updating satisfaction scores. Customer sentiment data flows back into the system through various channels (support tickets, surveys, social media), triggering automatic score recalculations that provide timely feedback about individual customer states without waiting for periodic surveys.
2Measurement precision
If traditional customer surveys are conducted after customer interactions, then customer satisfaction can be measured, but the measurement is delayed and not real-time
Solution Approach 1:
The system performs preliminary satisfaction assessment continuously in the background before formal surveys are needed. Customer satisfaction scores are pre-calculated based on existing interaction data, allowing the system to immediately determine customer sentiment status without waiting for post-interaction surveys. This preliminary scoring enables real-time decision-making.
Solution Approach 2:
The patent maintains continuous satisfaction measurement operations rather than periodic surveying. The system continuously monitors customer interactions, updates scores in real-time, and maintains an ever-current view of customer sentiment. This continuous action eliminates time delays by ensuring satisfaction data is always available without interruption or waiting periods.
3Measurement precision
If customer surveys are sent to all customers, then aggregated satisfaction data can be collected, but not all customers complete the surveys and global satisfaction cannot be accurately determined
Solution Approach 1:
The system enables automatic self-service satisfaction measurement where customer data from existing interactions (support tickets, purchase history, communication logs) is automatically harvested and processed. Customers don't need to actively participate in surveys; their satisfaction indicators are derived from their natural behavior and interaction patterns, eliminating the completion rate problem while maintaining data accuracy.
Solution Approach 2:
The patent uses multiple intermediary data sources (support interaction data, purchase behavior data, social media mentions, complaint data) to indirectly measure customer satisfaction. Rather than directly asking customers through surveys, the system uses these intermediary indicators to infer satisfaction levels, achieving global satisfaction measurement without requiring direct customer survey participation.
Data Source
AI summary
A system and method are disclosed for scoring an interaction over one or more channels by an end user and an entity by monitoring the communications over the channels and assigning penalties and scores based on topics associated with the communications.