Brief

🎯 Core Function: Automated Sentiment Analysis and Review Synthesis

This workflow creates an intelligent Telegram-driven bot that automatically mines customer opinions from Trustpilot, synthesizes the pros and cons using AI, and delivers a definitive purchase recommendation. It turns a simple product name input into a comprehensive, actionable review summary, essential for pre-purchase research or competitive intelligence.

Part 1: BrowserAct Workflow Description

This core module handles the dynamic searching and authenticated review data acquisition:

Dynamic Search Generation: The Agent receives the cleaned product keyword (e.g., "AwesomeApp") from Make.com. It then constructs a precise Google search query: [Product Name] Trustpilot reviews.

Targeted Site Navigation: The Agent performs the Google search, identifies the official Trustpilot review page link for the product from the search results, and clicks through directly.

Review Data Extraction: The Agent executes a scraping routine to extract all available raw review data, including the full review text, associated star ratings, and author names, specifically targeting the first two pages of customer reviews.

Data Transmission: The raw, unstructured review text and data are consolidated and returned as a single output string to the connected Make.com scenario.

Part 2: Automation Integration with Make.com

The Make.com scenario executes the user validation, data preparation, and final opinion synthesis:

Trigger & Validation: The workflow is triggered by a user request via Telegram. An initial AI node validates the user's intent and ensures a clean, extracted product name is ready for the next step.

Search Query Formulation: A subsequent AI node takes the clean product name and formats the perfect, precise search query required by the BrowserAct module (Part 1).

Data Mining: The system calls the BrowserAct node to execute the dynamic search, navigation, and scraping tasks outlined above.

AI Opinion Synthesis (Gemini): This is the core transformation. The final AI node receives the raw review data and, following a strict prompt, performs Opinion Mining:

Task: Summarize the product's overall reception.

Structure: Generates a clear, bulleted list of Upsides (Pros) and Downsides (Cons).

Conclusion: Provides a final, definitive purchase recommendation justified by the sentiment analysis.

Final Delivery: The resulting user-friendly text message, formatted with Telegram-compatible HTML, is delivered directly to the user via the Telegram Bot.

✨ Applicable Scenarios (Use Cases)

This bot is ideal for immediate sentiment analysis and due diligence for products and services:

Consumer Pre-Purchase Research: Users can instantly check the real-world reputation and identify the key flaws/strengths of any product before making a buying decision.

Competitive Intelligence: Businesses can quickly assess the public sentiment and common pain points of their competitors' products by simply typing in their names.

Market Opportunity Identification: Analysts can use the bot to identify neglected features or common critical complaints across an industry, highlighting potential product development opportunities.

Customer Service & Sales Support: Sales teams can use the bot to instantly retrieve objective pro/con summaries when discussing products with customers.

30-60credits per task (estimated)