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Houzz Scraper - Scrape Houzz Property Listings and Builder Data

RealdataAPI / houzz-scraper

Houzz Scraper is a powerful solution designed to extract valuable real estate and builder information from the Houzz platform. Using the Houzz Data Scraping API, businesses can efficiently scrape Houzz property listings and builder data including project details, builder profiles, reviews, ratings, locations, images, and pricing insights. This Houzz Scraper helps real estate analysts, market researchers, and property platforms gather structured data for competitive analysis and market intelligence. With the Houzz Data Scraping API, users can automate large-scale Houzz property data scraping, saving time while ensuring accurate and updated datasets. Companies can leverage this Houzz Scraper to monitor builder activities, analyze design trends, and build comprehensive real estate databases for strategic decision-making.

What is Houzz Data Scraper, and How Does It Work?

A Houzz Data Scraper is a specialized tool designed to automatically collect property and builder information from the Houzz platform. It extracts details such as project descriptions, builder profiles, ratings, reviews, images, and location data. The scraper works by sending automated requests to Houzz pages and parsing the HTML to gather structured information. Businesses can then store this data in databases or spreadsheets for analysis. By using a Houzz property data scraping API, companies can automate large-scale data extraction, ensuring accurate, consistent, and up-to-date datasets for real estate research, competitor monitoring, and property market intelligence.

Why Extract Data from Houzz?

Extracting data from Houzz helps businesses gain valuable insights into real estate trends, builder performance, and property demand. Market researchers, real estate agencies, and property platforms can analyze design trends, pricing strategies, and customer reviews to make better business decisions. Access to large datasets enables companies to track competitor activity and identify popular projects or locations. By using a Houzz real estate listings data scraper, organizations can collect comprehensive listing information such as project features, builder details, and client feedback, helping them create competitive strategies and improve their property offerings in the real estate market.

Is It Legal to Extract Houzz Data?

Data extraction from Houzz can be legal when performed responsibly and in compliance with the platform’s terms of service and applicable data regulations. Businesses should avoid scraping personal or restricted data and ensure they respect copyright policies and usage limitations. Ethical scraping practices include collecting publicly available information, following rate limits, and using the data for analytical or research purposes. Many companies rely on structured tools for Houzz property availability and pricing data scraping to monitor property trends and builder offerings while maintaining compliance with legal and ethical guidelines related to web data extraction.

How Can I Extract Data from Houzz?

To extract data from Houzz, businesses typically use automated scraping tools, APIs, or custom scripts that navigate Houzz pages and capture relevant information. The process usually includes identifying target pages, sending requests to retrieve page content, parsing the HTML structure, and exporting the collected data into usable formats such as CSV or JSON. Advanced tools also include proxy management, scheduling, and anti-blocking mechanisms for smooth extraction. A Houzz real estate data extractor simplifies this process by automating large-scale data collection, allowing companies to gather builder details, property images, project specifications, and customer reviews efficiently.

Do You Want More Houzz Scraping Alternatives?

While Houzz provides valuable design and property insights, businesses may also explore alternative platforms to gather broader real estate datasets. Other home design, property listing, and builder marketplaces often contain useful project information, pricing trends, and contractor profiles. Using multiple sources helps companies build richer datasets and improve market analysis. Data scraping tools and APIs allow businesses to collect and integrate data from several platforms efficiently. With Houzz property catalog data extraction, organizations can combine Houzz data with other property sources to develop deeper insights, strengthen research capabilities, and enhance real estate analytics strategies.

Input options

Our platform offers flexible input options that allow users to easily configure and manage their scraping requests. With the Houzz scraper, users can provide specific search URLs, property categories, location filters, builder profiles, or project pages to start the extraction process. This ensures accurate and targeted data collection based on business requirements. By using a Real-time Houzz property listings data API, companies can automatically collect updated property information, builder details, and design project data. The system is designed to efficiently Extract Houzz property listings and rental data, enabling businesses to gather structured datasets for real estate analysis, competitor monitoring, and market research.

Sample Result of Houzz Data Scraper

{
  "platform": "Houzz",
  "scrape_date": "2026-03-06",
  "results": [
    {
      "property_id": "HZ102394",
      "property_title": "Modern Luxury Villa Design",
      "builder_name": "UrbanSpace Builders",
      "location": "Los Angeles, California, USA",
      "property_type": "Residential Villa",
      "price_range": "$950,000 - $1,200,000",
      "availability_status": "Available",
      "rating": 4.8,
      "review_count": 124,
      "project_description": "Contemporary villa with open floor plan, smart home features, and eco-friendly materials.",
      "images": [
        "https://images.houzz.com/photo1.jpg",
        "https://images.houzz.com/photo2.jpg"
      ],
      "listing_url": "https://www.houzz.com/project/modern-luxury-villa"
    },
    {
      "property_id": "HZ102395",
      "property_title": "Minimalist Apartment Interior",
      "builder_name": "NextGen Design Studio",
      "location": "Austin, Texas, USA",
      "property_type": "Apartment",
      "price_range": "$350,000 - $420,000",
      "availability_status": "Available",
      "rating": 4.6,
      "review_count": 78,
      "project_description": "Minimalist apartment featuring Scandinavian interiors, natural lighting, and smart storage solutions.",
      "images": [
        "https://images.houzz.com/photo3.jpg",
        "https://images.houzz.com/photo4.jpg"
      ],
      "listing_url": "https://www.houzz.com/project/minimalist-apartment"
    }
  ]
}


Integrations with Houzz Scraper – Houzz Data Extraction

The Houzz Scraper easily integrates with various analytics platforms, databases, and business intelligence tools to streamline real estate data workflows. Businesses can connect the scraper with CRM systems, data warehouses, or visualization tools like dashboards to analyze trends and performance. These integrations help organizations transform raw data into actionable insights for market research and property analysis. By using a Houzz scraper for real estate market insights, companies can automatically gather valuable information on builders, design projects, and listings. The extracted data can also be organized into a structured Houzz Real Estate Dataset, enabling deeper analysis, reporting, and strategic decision-making.

Executing Houzz Data Scraping with Real Data API

Executing data extraction from Houzz becomes seamless with the powerful Houzz Scraper integrated into the Houzz Data Scraping API. Businesses can automate the process by sending API requests with specific search parameters such as project categories, builder profiles, or location filters. The scraper collects relevant information including property listings, builder details, reviews, images, and pricing insights. The extracted data is then delivered in structured formats like JSON or CSV for easy integration into analytics tools or databases. Using the Houzz Data Scraping API, companies can efficiently gather large-scale datasets for market research, trend analysis, and competitive intelligence.

You should have a Real Data API account to execute the program examples. Replace in the program using the token of your actor. Read about the live APIs with Real Data API docs for more explanation.

import { RealdataAPIClient } from 'RealDataAPI-client';

// Initialize the RealdataAPIClient with API token
const client = new RealdataAPIClient({
    token: '',
});

// Prepare actor input
const input = {
    "categoryOrProductUrls": [
        {
            "url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5"
        }
    ],
    "maxItems": 100,
    "proxyConfiguration": {
        "useRealDataAPIProxy": true
    }
};

(async () => {
    // Run the actor and wait for it to finish
    const run = await client.actor("junglee/amazon-crawler").call(input);

    // Fetch and print actor results from the run's dataset (if any)
    console.log('Results from dataset');
    const { items } = await client.dataset(run.defaultDatasetId).listItems();
    items.forEach((item) => {
        console.dir(item);
    });
})();
from realdataapi_client import RealdataAPIClient

# Initialize the RealdataAPIClient with your API token
client = RealdataAPIClient("")

# Prepare the actor input
run_input = {
    "categoryOrProductUrls": [{ "url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5" }],
    "maxItems": 100,
    "proxyConfiguration": { "useRealDataAPIProxy": True },
}

# Run the actor and wait for it to finish
run = client.actor("junglee/amazon-crawler").call(run_input=run_input)

# Fetch and print actor results from the run's dataset (if there are any)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
# Set API token
API_TOKEN=<YOUR_API_TOKEN>

# Prepare actor input
cat > input.json <<'EOF'
{
  "categoryOrProductUrls": [
    {
      "url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5"
    }
  ],
  "maxItems": 100,
  "proxyConfiguration": {
    "useRealDataAPIProxy": true
  }
}
EOF

# Run the actor
curl "https://api.realdataapi.com/v2/acts/junglee~amazon-crawler/runs?token=$API_TOKEN" \
  -X POST \
  -d @input.json \
  -H 'Content-Type: application/json'

Place the Amazon product URLs

productUrls Required Array

Put one or more URLs of products from Amazon you wish to extract.

Max reviews

Max reviews Optional Integer

Put the maximum count of reviews to scrape. If you want to scrape all reviews, keep them blank.

Link selector

linkSelector Optional String

A CSS selector saying which links on the page (< a> elements with href attribute) shall be followed and added to the request queue. To filter the links added to the queue, use the Pseudo-URLs and/or Glob patterns setting. If Link selector is empty, the page links are ignored. For details, see Link selector in README.

Mention personal data

includeGdprSensitive Optional Array

Personal information like name, ID, or profile pic that GDPR of European countries and other worldwide regulations protect. You must not extract personal information without legal reason.

Reviews sort

sort Optional String

Choose the criteria to scrape reviews. Here, use the default HELPFUL of Amazon.

Options:

RECENT,HELPFUL

Proxy configuration

proxyConfiguration Required Object

You can fix proxy groups from certain countries. Amazon displays products to deliver to your location based on your proxy. No need to worry if you find globally shipped products sufficient.

Extended output function

extendedOutputFunction Optional String

Enter the function that receives the JQuery handle as the argument and reflects the customized scraped data. You'll get this merged data as a default result.

{
  "categoryOrProductUrls": [
    {
      "url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5"
    }
  ],
  "maxItems": 100,
  "detailedInformation": false,
  "useCaptchaSolver": false,
  "proxyConfiguration": {
    "useRealDataAPIProxy": true
  }
}
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