Consumer Products — Customer Intent Classification for Enhanced Service Response

Overview

The primary purpose of this DAG is to extract and classify customer intents from interactions recorded in the CRM system, thereby enhancing the responsiveness of customer service teams. The workflow begins with the ingestion of data from multiple sources, including CRM interaction logs and IT Service Management (ITSM) tools. Once ingested, the data undergoes a normalization process to ensure consistency and quality across all records. Following normalization, a validation step is implemented to

The primary purpose of this DAG is to extract and classify customer intents from interactions recorded in the CRM system, thereby enhancing the responsiveness of customer service teams. The workflow begins with the ingestion of data from multiple sources, including CRM interaction logs and IT Service Management (ITSM) tools. Once ingested, the data undergoes a normalization process to ensure consistency and quality across all records. Following normalization, a validation step is implemented to assess the quality of the data, ensuring that only accurate and relevant intents are classified. The classification process utilizes machine learning algorithms to categorize intents into predefined categories, which allows for more targeted responses from customer service representatives. The results of this classification are then published to a performance monitoring dashboard, which provides real-time insights into classification accuracy and intent distribution. Additionally, alert mechanisms are in place to notify stakeholders in the event of classification failures, ensuring prompt corrective actions can be taken. Key performance indicators (KPIs) such as classification accuracy, processing time, and intent recognition rates are monitored continuously to assess the effectiveness of the system. The business value of this DAG lies in its ability to streamline customer service operations, reduce response times, and ultimately enhance customer satisfaction by ensuring that inquiries are handled with greater precision and relevance.

Part of the AI Assistants & Contact Center solution for the Consumer Products industry.

Use cases

• Improved customer satisfaction through tailored responses
• Increased operational efficiency in customer service
• Reduced response times for customer inquiries
• Enhanced data-driven decision-making capabilities
• Ability to identify trends in customer intents over time