Telecom — User Feedback Collection and Analysis Pipeline

Overview

The primary purpose of this DAG is to streamline the collection and analysis of user feedback regarding summaries produced within the Telecom sector. It integrates various data sources, including user surveys and sentiment analysis tools, to evaluate user satisfaction effectively. The ingestion pipeline begins with the collection of survey responses, which are then processed to extract sentiment insights. This processing involves natural language processing techniques to gauge user sentiment, fo

The primary purpose of this DAG is to streamline the collection and analysis of user feedback regarding summaries produced within the Telecom sector. It integrates various data sources, including user surveys and sentiment analysis tools, to evaluate user satisfaction effectively. The ingestion pipeline begins with the collection of survey responses, which are then processed to extract sentiment insights. This processing involves natural language processing techniques to gauge user sentiment, followed by data aggregation to compute satisfaction scores. Quality controls are implemented at each stage to ensure the accuracy of sentiment analysis and response rates. The outputs of this DAG include comprehensive reports detailing user satisfaction metrics, response rates, and actionable insights for improving summary generation. Key performance indicators (KPIs) monitored include the response rate of surveys and the overall user satisfaction score. By utilizing this feedback, Telecom organizations can refine their summary generation processes, leading to enhanced user engagement and satisfaction. Ultimately, this DAG adds significant business value by fostering a user-centric approach to content generation, ensuring that summaries meet user expectations and contribute to improved service delivery.

Part of the Knowledge Portal & Ontologies solution for the Telecom industry.

Use cases

• Enhances user satisfaction through targeted feedback analysis
• Improves summary quality based on user insights
• Increases engagement by addressing user concerns
• Facilitates data-driven decision-making in content generation
• Strengthens customer relationships through responsive adjustments