Intelligent Customer Feedback Sentiment Analysis and Archiving Workflow

This workflow automatically receives customer feedback online and utilizes OpenAI for sentiment analysis to intelligently assess emotional tendencies. The analysis results are then combined with the feedback content and archived in Google Sheets. This automation not only enhances the efficiency of the customer service team's response to feedback but also helps the business quickly identify customer satisfaction levels and the urgency of feedback, enabling a deeper understanding of the customer voice and driving the optimization of services and products.

Workflow Diagram
Intelligent Customer Feedback Sentiment Analysis and Archiving Workflow Workflow diagram

Workflow Name

Intelligent Customer Feedback Sentiment Analysis and Archiving Workflow

Key Features and Highlights

This workflow automatically receives customer feedback submitted via an online form, utilizes OpenAI for sentiment analysis to intelligently determine the emotional tone of the feedback (e.g., positive, negative, neutral), and merges the analysis results with the original feedback content. The combined data is then automatically archived into a Google Sheets spreadsheet for easy subsequent organization, statistical analysis, and tracking.

Core Problems Addressed

Traditional customer feedback collection methods typically only record textual content without automatic recognition and classification of sentiment. This limitation makes it difficult for customer service teams to quickly assess the urgency of feedback and customer satisfaction, thereby affecting response efficiency and service quality. This workflow enables automatic sentiment classification, helping enterprises better understand customer voices and enhance customer experience management.

Application Scenarios

  • Automated collection and analysis of customer feedback in customer service centers
  • Sentiment trend statistics and archiving for product or service improvements
  • Rapid classification of customer opinion sentiment in market research
  • Internal employee satisfaction surveys and data management within enterprises

Main Process Steps

  1. Customers submit feedback through a customized online form, including name, feedback type, detailed content, and contact information.
  2. The form triggers the workflow, which automatically calls the OpenAI API to perform sentiment analysis on the feedback text.
  3. The sentiment analysis results are merged with the original feedback content.
  4. The merged data is automatically appended to a Google Sheets spreadsheet, creating a structured customer feedback archive.
  5. Enterprise personnel can access the Google Sheets at any time to review detailed feedback and sentiment classifications to support decision-making.

Involved Systems or Services

  • n8n Automation Platform (workflow triggering and node execution)
  • OpenAI (sentiment analysis API)
  • Google Sheets (feedback data storage and management)
  • Customized Online Form (customer feedback collection)

Target Users and Value

  • Customer Service Teams: Improve feedback processing efficiency and quickly identify negative feedback requiring priority attention.
  • Product Managers and Market Researchers: Gain customer sentiment data support to optimize product and service strategies.
  • Enterprise Managers: Drive data-informed decisions and enhance customer satisfaction monitoring capabilities.
  • Automation Enthusiasts and SMEs: Achieve intelligent customer feedback management with low barriers, saving labor costs.

This workflow creates an efficient and intelligent closed loop for customer feedback, enabling enterprises to gain real-time insights into customer needs and emotions, thereby driving continuous improvement in services and products.