Sentiment Analysis Report
To analyze customer conversations, our Workflow feature plays a crucial role. Follow these steps to extract & analyze customer conversations:
-
Pull Data: Begin by pulling data containing the content of customer conversations.
-
Data Structuring: If the data isn't pre-structured, utilize the "Ask AI about dataset" building block to organize conversations appropriately. Instruct the AI to extract key fields such as CustomerID.
-
Sentiment Analysis: Use the "Ask AI about a row" building block to classify conversation content into ten sentiment categories.
-
Dataset Organization: Once analyzed, you'll have an organized dataset featuring columns for "CustomerID," "Message," "Category," "Date," "Reason," and mention of a "Discount Code."
-
Filtering: Apply a filter to retain only the rows where the category is identified as 'Abandonments.'
-
Conclusion: Wrap up the workflow by incorporating the "Send to Email" block for seamless sharing of insights.
By following these steps, businesses can gain valuable insights from customer conversations, enabling them to make informed decisions and improve overall customer satisfaction.
