Build Your First Data Scraper Workflow in 5 Minutes

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0. Before You Start: Core Concepts

• Workflow (The Blueprint): The complete definition of your automated process (like a digital SOP). It is a static file you design and save.
• Node (The Building Block): The individual instructions within a workflow. You map manual actions to specific nodes:
  • Open URL 👉 Visit Page
  • Type 👉 Input Text
  • Click 👉 Click Element
• Task (The Runtime Instance): A single execution record. When you hit “Run” on a specific Workflow with specific parameters, it creates a Task that generates your data/CSV.

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1. Open the Workflow Builder

1. Locate the “AI Workflow Builder” card in the center area.
2. Click it to open the Workflow Build page (the canvas where we’ll add nodes).

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2. Example Setup & Logic

• Country: e.g., USA
• Area: e.g., Avalon, CA

1. Open https://www.google.com/maps
2. Search {Country} {Area}
3. Click search icon
4. Click Nearby
5. Click Restaurant
6. Extract list data

• name
• full_address
• star_rating
• review_count
• average_price_per_person_range

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3. Step-by-Step Setup (Node Orchestration)

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Step 1 – Start Node: Define Input Parameters

1. On the canvas, click the Start node.
2. In Input Parameters, add:
   • Name: Country | Default Value: USA
   • Name: Area | Default Value:: Avalon, CA

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Step 2 – Visit Page: Open Google Maps

1. Click + on the canvas (or right-click) and choose Visit Page.
2. Connect it after Start.
3. Set URL to:
   Copy

   Ask AI

   https://www.google.com/maps
   
   

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Step 3 – Input Text: Search for the Location

1. Add an Input Text node and connect it after Visit Page.
2. In the page preview/selector, target the top search bar.
3. In Text to Input, enter: Country Area (This references the Start parameters).

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Step 4 – Click Element: Navigate to Restaurants

1. Search: Click the magnifying-glass icon.
2. Nearby: Click the “Nearby” button.
3. Restaurant: Click the “Restaurant” category.

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Step 5 – Extract Data: Scrape the Restaurant List

1. Add an Extract Data node after the last Click Element node.
2. In the left restaurant list, select one full restaurant item as the sample.
3. Configure fields to extract:
   • name
   • full_address
   • star_rating
   • review_count
   • average_price_per_person_range

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Step 6 – Finish: Output Data as CSV

1. Add a Finish: Output Data node and connect it after Extract Data.
2. In the output settings:
   • Output Format: CSV
   • Enable: “Output as a file”

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4. Publish & Run

1. Publish Version: Click the Publish button (top-right corner) and select Publish as New Version to save your current configuration.
2. Enter Run Mode: Click the Run tab (located next to the Build tab).
3. Set Parameters:
   • Country: USA
   • Area: Avalon, CA
4. Execute: Click Start Run and watch the nodes execute one by one.

1. All steps show Succeeded / ✔.
2. The run result shows a downloadable CSV file.
3. The CSV contains rows like:

name,full_address,star_rating,review_count,average_price_per_person_range
Bluewater Avalon,306 Crescent Ave,4.3,2342,$30–50
Buffalo Nickel Inc,57 Pebbly Beach Rd,4.6,646,$20–30
...

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5. Common Roadblocks (Quick Fixes)

• CSV is empty or has very few rows:
  • Check the sample in Extract Data: it should be a full list item, not a tiny sub-element.
  • Wait for load: Add a short wait before Extract Data if the list loads slowly.
• Click Element does nothing:
  • Re-select the actual clickable element (button/text) in the Click Element node.
  • Confirm node order: Search → Nearby → Restaurant.
• Run error and not sure why:
  • Check URL in Visit Page is exactly https://www.google.com/maps.
  • Ensure Run parameters (Country/Area) are filled.
  • Ensure no node has missing config (Click Element, etc.).

Support: If it still fails, contact support via Discord with:

• A short description of your goal.
• Screenshot of the failing error.
• Task ID of the execution.

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8. Next Steps

1. Reuse it with new locations Run again with:
   • Country: USA, Area: New York
   • Country: Japan, Area: Shibuya