Hidden API Web Scraping: How to Extract Real Estate Data Automatically

Web scraping provides powerful methods to extract valuable data from websites, but identifying hidden APIs can take your data collection to the next level. This approach offers a more reliable and efficient method compared to traditional HTML scraping techniques.

Let’s explore how to identify and utilize hidden APIs to extract real estate listing data, then automate the process using make.com.

Finding Hidden APIs in Website Network Requests

The first step is identifying the API endpoints that contain the data you need. When browsing a real estate website like crexc.com:

1. Navigate to the page containing your desired data (such as property listings in Los Angeles)
2. Open your browser’s Developer Tools by right-clicking and selecting ‘Inspect’ or using Ctrl+Shift+I
3. Select the Network tab and refresh the page to capture all requests
4. Look for API requests that might contain your target data

When examining network requests, focus on those with promising names like ‘search’ or ‘listings’. The preview tab will show if the response contains useful data such as property descriptions, prices, and other details.

Identifying the Key API Components

Once you’ve found the appropriate request, note these critical elements:

• The request URL (e.g., api.crexy.com endpoints)
• Request method (POST in our example)
• Headers, especially the Authorization token which acts as an access key
• User-Agent string to appear as a legitimate browser
• Request payload (the JSON data sent with the request)

The Authorization header is particularly important as it authenticates your request to the server. Without it, your request will likely be rejected.

Setting Up Automation in make.com

With the API details identified, you can create an automated workflow:

1. Configure the HTTP Request

Use the HTTP module in make.com with these settings:

• URL: The API endpoint identified in DevTools
• Method: POST (or whatever method the API uses)
• Headers: Include Authorization, User-Agent, and any other required headers
• Body Type: Raw with Content-Type as JSON
• Payload: Copy the request payload from DevTools

2. Process the Response Data

After receiving data from the API:

• Use an Iterator module to process each item in the returned array
• Map the data fields to your desired output format

3. Store Data in Google Sheets

Configure the Google Sheets module to:

• Connect to your spreadsheet
• Select the appropriate sheet
• Map the data fields to columns
• Add optional delay between records using the Tools module’s Sleep function

Running and Scheduling Your Automation

Once configured, you can run your scenario manually to test it or set it to run automatically on a schedule. Make.com allows you to set intervals such as every 15 minutes, hourly, or daily depending on how frequently you need fresh data.

Remember that make.com charges based on operations used, so optimize your automation to avoid unnecessary processing. For high-volume data extraction, consider adding filters or limits to your requests.

Benefits of the Hidden API Approach

This method offers several advantages over traditional web scraping:

• More stable: Less affected by website UI changes
• Higher performance: Direct data access without parsing HTML
• Better data quality: Structured JSON data instead of extracted text
• Lower detection risk: Uses the website’s own API mechanisms

By leveraging hidden APIs, you can build robust data collection systems that provide reliable information for your business intelligence, market research, or analytical needs.