BrowserAct Product Advisor Workflow

Make AI Product Insight Machine enables teams to transform simple Telegram messages into structured, decision-ready product insights — without manually searching Google, Reddit, or reading dozens of scattered reviews.

When researching digital products, customer opinions are often fragmented across multiple platforms, making it difficult and time-consuming to form a clear, unbiased understanding. This Make-powered workflow solves that problem by orchestrating AI intent detection, automated browser data collection, and insight synthesis into a single, seamless flow.

The workflow is triggered when a user submits a product name or description via Telegram. Make first uses AI to determine whether the message represents a genuine product research request. If confirmed, Make generates a clean, focused search query and triggers an automated BrowserAct workflow to collect public customer feedback from Google and Reddit. The collected data is then processed by AI to produce a structured insight report, which is delivered back to the user directly in Telegram.

Input
Product name or product description (via Telegram)

Output
A concise product insight report including:

• Product summary
• Key strengths (pros)
• Common complaints (cons)
• Final recommendation

This Make automation is ideal for founders, product managers, marketers, and researchers who need fast, data-driven product insights for validation, competitive analysis, and decision-making.

Typical use cases include:

• Evaluating SaaS tools before purchase
• Comparing competing digital products
• Monitoring customer sentiment during product research

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. • Product overview
   • Pros and cons (bulleted)
   • 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.