Public Sector — User Intent Classification for Enhanced Interaction

Overview

The primary purpose of this DAG is to classify user intents derived from queries submitted via a public sector business portal. By analyzing these intents, the system aims to enhance the interaction quality between users and agents, ultimately improving service delivery. The data sources for this pipeline include user query logs, historical interaction data, and agent response templates. The ingestion pipeline first collects and preprocesses these data sources to ensure they are ready for analys

The primary purpose of this DAG is to classify user intents derived from queries submitted via a public sector business portal. By analyzing these intents, the system aims to enhance the interaction quality between users and agents, ultimately improving service delivery. The data sources for this pipeline include user query logs, historical interaction data, and agent response templates. The ingestion pipeline first collects and preprocesses these data sources to ensure they are ready for analysis. The processing steps involve several key stages: first, the system tokenizes the user queries to extract relevant features. Next, a machine learning model is applied to classify the intents based on predefined categories. Quality controls are implemented at this stage to validate the accuracy of classifications, ensuring that only relevant intents are forwarded to the next step. The results are then aggregated and analyzed to provide insights into user behavior and agent performance. The outputs of this DAG include classified intent reports, agent performance metrics, and user satisfaction scores. Monitoring KPIs such as satisfaction rate and response time are crucial for assessing the effectiveness of the classification process. By leveraging these insights, public sector organizations can optimize their pricing strategies and improve overall service efficiency, ultimately delivering greater value to users.

Part of the Pricing Optimization solution for the Public Sector industry.

Use cases

• Improved user-agent interaction leading to higher satisfaction
• Faster response times through accurate intent classification
• Enhanced document guidance based on user needs
• Data-driven insights for continuous service improvement
• Optimized pricing strategies based on user intent analysis