ManualTrigger Automate
For the ManualTrigger Automate workflow, streamline the extraction and analysis of Trustpilot reviews. This automated process collects and organizes reviews, applies advanced clustering algorithms to identify key themes, and generates actionable insights. It efficiently exports results to Google Sheets, enabling businesses to understand customer sentiment and improve their services based on detailed feedback analysis.
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Workflow Overview
For the ManualTrigger Automate workflow, streamline the extraction and analysis of Trustpilot reviews. This automated process collects and organizes reviews, applies advanced clustering algorithms to identify key themes, and generates actionable insights. It efficiently exports results to Google Sheets, enabling businesses to understand customer sentiment and improve their services based on detailed feedback analysis.
This workflow is ideal for:
- Business Analysts looking to gain insights from customer reviews.
- Product Managers wanting to understand customer feedback and improve products.
- Marketing Teams focused on enhancing brand reputation through customer sentiment analysis.
- Data Scientists interested in clustering algorithms and natural language processing.
- Small Business Owners who want to leverage customer feedback to enhance their services.
This workflow addresses the challenge of extracting valuable insights from Trustpilot reviews. It automates the process of scraping reviews, analyzing sentiment, and clustering similar feedback. By utilizing advanced algorithms, it helps in identifying common themes and suggestions from customers, enabling businesses to make informed decisions based on real customer experiences.
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Clear Existing Reviews: The workflow begins by removing any previous reviews stored in the Qdrant vector store for the specified company, ensuring a fresh start.
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Fetch Trustpilot Pages: It retrieves the latest reviews from Trustpilot for the specified company, scraping up to 3 pages of reviews.
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Extract Reviews: The HTML content is processed to extract relevant data such as review author, rating, title, text, and dates.
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Prepare Data for Vector Storage: The extracted reviews are formatted and stored in a structured format suitable for further analysis.
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Store Reviews in Qdrant: The reviews are vectorized and inserted into the Qdrant vector store, allowing for efficient similarity searches and clustering.
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Find Reviews: The workflow retrieves stored reviews based on specific criteria, including date ranges and company ID.
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Apply K-means Clustering: A K-means clustering algorithm is applied to group similar reviews, facilitating the identification of common themes.
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Generate Insights: The clustered reviews are analyzed using a language model to produce insights, sentiments, and suggested improvements.
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Export to Google Sheets: Finally, the insights and raw responses are exported to a Google Sheet for easy access and reporting.