Feedback System Aggregating Customer Sentiment Data
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Solution Overview
Problem
Current systems face challenges in effectively managing and analyzing customer experience data to provide actionable insights for improving business operations and customer satisfaction, as they struggle with data aggregation, storage, and retrieval, while also efficiently communicating insights to authorized users.
Innovation Solution
A cloud-based feedback and rating system that enables employees to anonymously rate coworkers, with a web interface for generating actionable data analytics, including sentiment ratings and surveys, which can be aggregated and displayed in organizational charts to inform management decisions and HR strategies, and a customer-facing system that uses a 1-5 scale with clickable attribute tags for easy feedback collection and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If customer experience data is collected and aggregated, then actionable insights for improving business operations can be obtained, but the complexity of managing, storing, and retrieving the data increases
Solution Approach 1:
The patent introduces an intermediary processing layer that aggregates and structures customer experience data before storage. This intermediary system transforms raw feedback into standardized formats, reducing the complexity of data management while preserving actionable insights. The intermediary layer includes processing modules that normalize data from multiple sources and convert it into a unified structure for easier retrieval and analysis.
Solution Approach 2:
The data management system is segmented into modular components including data collection modules, processing modules, storage modules, and retrieval modules. Each component handles specific aspects of the data lifecycle independently, reducing overall system complexity. The segmentation allows parallel processing of different data types and enables independent optimization of each module without affecting the entire system.
2Loss of information
If comprehensive customer experience data is stored, then better analytics and reporting can be generated, but data retrieval efficiency decreases
Solution Approach 1:
The system performs preliminary indexing and categorization of customer experience data during the ingestion phase. Data is pre-processed and organized into structured formats with metadata tags that enable rapid retrieval. This preliminary action includes creating summary statistics and aggregating data at multiple levels (individual, department, organizational) so that common queries can be answered without scanning the entire dataset.
Solution Approach 2:
The patent implements multi-dimensional indexing of data with hierarchical organization structures. Data can be retrieved along different dimensions (time, department, customer segment, feedback type) simultaneously. This dimensional organization allows the system to efficiently respond to various query types by navigating through the most relevant dimension rather than searching the entire dataset, significantly reducing retrieval time while maintaining comprehensive data storage.
3Loss of information
If detailed analytics are provided to authorized users, then informed management decisions can be made, but the difficulty of communicating insights effectively increases
Solution Approach 1:
The reporting system provides localized and role-specific views of analytics tailored to different authorized users. Each user receives insights relevant to their specific role, department, and responsibilities rather than a uniform comprehensive report. The system automatically adjusts the detail level, metrics, and presentation format based on the user's profile, making complex analytics accessible and actionable for each stakeholder without overwhelming them with irrelevant information.
Solution Approach 2:
The analytics presentation is dynamic and adaptive, automatically adjusting the level of detail, aggregation, and visualization based on user interactions and preferences. The system can drill down from high-level summaries to detailed analyses as users explore, and can reformat insights based on the communication context. This dynamic adaptation simplifies the communication of complex insights by presenting them in the most appropriate format for each specific interaction scenario.
Data Source
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AI summary
The present technology discloses methods, systems, and non-transitory computer-readable media for receiving ratings data, the received ratings data comprising responses to a survey associated with one or more customers of an enterprise and presenting a fixed number of attributes; aggregating the received ratings data; generating a report based on the aggregated ratings data; and generating a navigable interface comprising the generated report, the navigable interface accessible to an authorized user and comprising tabs, each tab interactable to display a respective portion of the generated report.