How to scrape real estate data from Cafeland using the Minexa.ai extension

Cafeland is one of Vietnam's main real estate portals, and its urban development project listings for Hai Phong carry a useful mix of investor details, sale status, geo-coordinates, and direct links to transaction pages. Getting that data into a spreadsheet manually is slow. This walkthrough shows how to do it in a few minutes using the Minexa.ai Chrome extension.

Watch the full tutorial first

The video below covers the complete extraction from start to export. Watch it once before going through the steps.

https://www.youtube.com/watch?v=Kk8Whkm8cz4

Step 1: Open Minexa.ai and navigate to Cafeland

After installing the extension, open the Minexa.ai home page to confirm it is active in your browser.

Then navigate to cafeland.vn/du-an/khu-do-thi-tai-hai-phong/ and let the page fully load before opening the extension.

Step 2: Confirm you are on the right page

Click the Minexa.ai extension icon. The popup will ask you to confirm you are on the page containing the data you want to extract.

Step 3: Review pagination detection

Minexa.ai automatically detects how the site loads additional results. It identifies the next page button and shows you what it found before continuing.

Step 4: Choose list or list with details

You can extract only the listing cards, or follow each project link and pull the full detail page data as well. For most market research tasks, the list alone covers investor name, location, sale status, and direct URLs.

Step 5: Start the scraping job

Select your scraping mode. The simple scenario handles standard listing pages like this one without any additional configuration.

Minexa.ai then highlights the full container holding all listing cards on the page automatically.

Step 6: Review extracted fields

After selecting the container, Minexa.ai surfaces all detected data points. You can navigate through them using the prev/next controls before finalising.

Sample extracted data

Here is what two records look like once extracted:

[
  {
    "housing_project": "Seoul Ecohomes: Du an khu do thi tai Hai Phong",
    "company_name": "Cong ty Co phan Khu cong nghiep Sai Gon - Hai Phong",
    "company_location": "tren truc Quoc lo 10, An Phong, Hai Phong",
    "status": "Dang mo ban",
    "project_link": "https://cafeland.vn/du-an/seoul-ecohomes-...",
    "map_url": "https://map.cafeland.vn/tin-du-an/20.857.../5516/"
  },
  {
    "housing_project": "Thanh Dong Metropolis: Khu do thi tai Hai Phong",
    "company_name": "Cong ty Co phan Dau tu Bat dong san Thanh Dong",
    "company_location": "Thach Khoi, Hai Phong",
    "status": "Dang mo ban",
    "project_link": "https://cafeland.vn/du-an/thanh-dong-metropolis-...",
    "map_url": "https://map.cafeland.vn/tin-du-an/20.886.../5469/"
  }
]

Step 7: Export your data

Once the job finishes, export to Excel or JSON directly from the results screen. Get started with Minexa.ai to run your first extraction today.

For more on extracting property listing data, see: Scraping real estate data: what actually works and where most pipelines break.