1. **Collect Customer Feedback**: Use n8n to gather feedback by polling from different sources, such as Twitter, Zendesk, or Google Forms.
2. **Store Feedback Details**: Store the received customer feedback in Google Sheets or Airtable, using n8n’s dedicated nodes for these platforms.
3. **Sanitize and Preprocess Data**: Use a Python script within n8n to cleanse and preprocess the customer feedback data for subsequent analysis.
4. **Perform Sentiment Analysis**: Send the preprocessed data to the OpenAI API through n8n’s HTTP Request node for sentiment analysis.
5. **Categorize Customer Feedback**: Utilize natural language processing (NLP) libraries like NLTK or spaCy in Python to classify the feedback into different categories.
6. **Aggregate Feedback Data**: Quantify the feedback data based on the identified categories and sentiment analysis results, using Python’s pandas library.
7. **Visualize Trends**: Use Python’s matplotlib or seaborn libraries to create visualizations that highlight important trends in the customer feedback data.
8. **Generate a Comprehensive Report**: Compile the insights and visualizations into a digestible report format using Python’s ReportLab library.
9. **Notify Stakeholders**: Leverage n8n’s Slack API or Email nodes to alert stakeholders with the report summary and a link to the full report.
10. **Create an Action Item List**: Use the insights from the report to develop action items for improvement and integrate with project management tools via suitable n8n nodes for seamless tracking.
This workflow is flexible, scalable, and error-resistant, offering a valuable approach to analyzing customer feedback for businesses of any size. Ensure each node is configured with appropriate error handling, handle private data compliantly, and securely store credentials containing sensitive data using n8n’s credentials feature.
