BrowserAct Product Advisor Workflow

A Make.com Workflow for Automated Product Research & Recommendation

BrowserAct Product Advisor Workflow helps users quickly understand real user sentiment and product quality signals without manually browsing Google, Reddit, or reading dozens of scattered reviews.

When researching a product, opinions and feedback are often fragmented across multiple platforms, making it time-consuming and difficult to form a balanced, data-driven decision. BrowserAct Product Advisor Workflow replaces this manual process with an end-to-end automation orchestrated entirely inside Make, turning a simple chat message into a structured product insight report.

The workflow starts when a user sends a product name or short description to a Telegram bot. Make coordinates AI-driven intent detection, keyword generation, automated review discovery via BrowserAct, structured data extraction, and final insight synthesis—delivering a ready-to-use product recommendation directly back to Telegram.

What Does BrowserAct Product Advisor Workflow Do?

BrowserAct Product Advisor Workflow enables founders, product managers, marketers, and researchers to automatically collect, analyze, and summarize public product reviews and discussions related to a specific product—without manual searching, opening multiple tabs, or copy-pasting content.

Customer opinions are scattered across Google search results, Reddit threads, and review pages. Manually comparing these sources is repetitive, slow, and difficult to scale. BrowserAct Product Advisor Workflow centralizes this entire process by combining AI decision logic, browser automation, and structured analysis inside Make.

Once triggered, the workflow evaluates the user’s intent, generates a clean product search query, runs a BrowserAct automation to gather public feedback, and produces a concise insight report with clear pros, cons, and a final recommendation.

Key Features of BrowserAct Product Advisor Workflow

• Telegram-Based Trigger
  Start the workflow by sending a product name or description directly to a Telegram bot.
• AI-Powered Intent Detection
  Uses AI inside Make to determine whether the message represents a genuine product research request before continuing.
• AI-Driven Keyword Generation
  Converts natural language input into a focused, automation-ready product search query.
• Automated Review Collection
  Uses BrowserAct within Make to search Google and Reddit and collect public customer feedback automatically.
• Insight-Focused Data Extraction
  Aggregates review content into a structured format suitable for AI analysis.
• Structured Parsing & Processing
  Processes collected data inside Make for stable, scalable execution.
• AI Insight Synthesis
  Generates a clear product summary with strengths, weaknesses, and a final recommendation.
• Telegram Delivery
  Sends the final product insight report directly back to Telegram for fast review.
• Fully No-Code Automation
  Built entirely with Make and BrowserAct—no scripts or custom code required.

What Data Can You Collect?

With BrowserAct Product Advisor Workflow, you can collect publicly available product feedback data, including:

Public Review & Discussion Data

• User opinions and comments
• Common complaints and pain points
• Frequently mentioned strengths
• Overall sentiment trends
• Contextual discussion insights from Reddit and Google results

How to Use BrowserAct Product Advisor Workflow in One Click

Using BrowserAct Product Advisor Workflow requires no manual setup or technical configuration. Once deployed in Make, the entire process can be triggered with a single action.

Simply send a product name or description to the connected Telegram bot. The workflow automatically detects intent, runs the review discovery process, analyzes the data, and delivers a structured product insight report back to Telegram—everything runs in the background.

Why Use Automated Product Insight?

Product decisions are often influenced by incomplete or biased information. Manually reading reviews across multiple platforms is inefficient and difficult to scale.

Automating this process allows teams to:

• Quickly understand real user sentiment
• Compare products more objectively
• Reduce research time dramatically
• Focus on decision-making instead of information gathering

BrowserAct Product Advisor Workflow enables faster, clearer, and more confident product decisions using AI-driven automation.

Input & Output

Input

• Product name or short description sent via Telegram

Output

• A Telegram message containing:
• • Product summary
  • Pros and cons (bulleted)
  • Final recommendation

Who Is BrowserAct Product Advisor Workflow For?

BrowserAct Product Advisor Workflow is ideal for:

• Founders and startup teams
• Product managers and researchers
• Marketers conducting competitive analysis
• Analysts validating product ideas or tools

Working Principle (How it works)

1. Trigger (Telegram)
   The workflow starts when a user sends a product name or product description to a Telegram bot. Telegram acts as the real-time entry point for the Make scenario.
2. Intent Gating (AI)
   Make uses an AI module to determine whether the message represents a digital product research request (e.g. reviews, quality, or comparison).
   If the intent is unclear or unrelated, the workflow stops and prompts the user to provide clearer product information.
3. Search Query Generation (AI)
   Once the intent is confirmed, Make converts the user’s natural language message into a clean, focused search keyword or phrase suitable for automated data collection.
4. Review Collection (BrowserAct)
   Make triggers a BrowserAct automation workflow using the generated keyword. BrowserAct searches Google and Reddit, navigates relevant pages, and aggregates public customer feedback into a structured output.
5. Insight Synthesis (AI)
   Make sends the collected review data to an AI module, which analyzes the content and generates a Telegram-ready insight report, including:
6. 1. Product overview
   2. Pros and cons (bulleted)
   3. Final recommendation
6. Result Delivery (Telegram)
   The final insight report is sent back to the user in Telegram, completing a fully automated, conversational product research loop.