Library / Monitoring, Ops & Incidents
Monitoring, Ops & Incidents
Monitor Competitor Product Launches and Email R and D
Every day at 7:00, an OpenAI agent scrapes competitor product reviews and launches from The Verge through Bright Data MCP, logs them in Sheets and emails your team.
What it does
# 🛠️ Monitor Competitor Product Launches (The Verge) > 🔄 Automated n8n workflow using Bright Data MCP to scrape reviews & notify R\&D team --- ## 🔶 SECTION 1: Schedule & Scrape Target Configuration 🧩 Nodes: * ⏰ Daily Check (7AM) * 🛠 Set Scrape Target (Verge Reviews) --- ### 🧠 What’s Happening: This section controls when and what to scrape. #### ⏰ Schedule Trigger * Automatically runs the workflow every morning at 7AM. * No manual checking needed! #### 🛠 Edit Fields * Sets the target scraping page: https://www.theverge.com/reviews * You can easily switch this to other competitor sites (like TechCrunch or Wired) later. --- ### 💡 Why it matters: This is where you customize your intelligence source. Just change the URL or keyword once — no coding needed. --- ## 🤖 SECTION 2: Agent-Powered Scraping with Bright Data 🧩 Node: * 🤖 Bright Data Scraper Agent 🔗 Sub-nodes: * 🔮 OpenAI Chat Model * 🧩 MCP Client (Bright Data Tool) * 📦 Structured Output Parser --- ### 🧠 What’s Happening: This is the heart of the automation — using a powerful AI agent connected to Bright Data’s scraping infrastructure. #### 🤖 AI Agent * Uses an OpenAI agent that understands your instructions. * Connects to Bright Data MCP to bypass anti-bot systems and extract clean product data. * Scrapes: * 📦 Product Title * 📅 Release Date * 📝 Short Summary * 🔗 URL (relative, so we'll fix that later) #### 📦 Structured Output Parser * Parses the AI agent’s response into structured JSON — ready for automation. --- ### 💡 Why it matters: Even a beginner can now use AI + Bright Data to scrape dynamic sites that normally block scrapers. --- ## 🧾 SECTION 3: Split & Format Each Review 🧩 Node: * 🧾 Split & Format Each Review --- ### 🧠 What’s Happening: This Code Node takes the array of product reviews and splits them into one item each. #### Code Features: * Converts relative URLs to full links (e.g., /xyz → https://www.theverge.com/xyz) * Outputs 10 clean JSON objects, one per review. javascript return items.map(review => { return { json: { title: review.title, url: "https://www.theverge.com" + review.url, release_date: review.release_date, summary: review.summary } }; }); --- ### 💡 Why it matters: This lets you send individual emails and store individual entries — great for reporting, filtering, and team alerts. --- ## ✉️📊 SECTION 4: Notify & Log the Insights
The steps
- OpenAI Chat Model
- MCP Client
- ⏰ Daily Check (7AM)
- 🛠 Set Scrape Target (Verge Reviews)
- 🤖 Bright Data Scraper Agent
- 🧾 Split & Format Each Review
- 📤 Email R&D: Product Alerts
- 📊 Log to Google Sheet (Review History)
- Auto-fixing Output Parser
- OpenAI Chat Model1
- Structured Output Parser1
Similar automations
Monitoring, Ops & IncidentsTrack Competitor Prices Weekly with Bright Data and OpenAI11 stepsMonitoring, Ops & IncidentsMonitor Competitor Prices Daily with Sheets and Telegram15 stepsWeb Scraping & ResearchTrack Daily Product Hunt Launches in Google Sheets9 stepsMonitoring, Ops & IncidentsMonitor Competitor Pricing with Airtop and Alert Slack8 steps