Houzz Product Scraper

Extract product data from Houzz with fast, automated collection. Gather key fields such as price, ratings, review counts, brand, and product URLs in a structured dataset. Built for market research, catalog analysis, and ongoing competitor monitoring.

Features

• Targeted keyword search — Collect products based on search phrases like sofa, dining table, or outdoor furniture.
• Adjustable collection limits — Control total records with results_wanted and page depth with max_pages.
• Structured product fields — Get clean fields for pricing, ratings, sale status, product type, SKU, and more.
• Duplicate reduction — Avoid repeated product entries when traversing multiple result pages.
• Sale insight support — Capture both current price and original price when an item is discounted.
• Proxy-ready runs — Configure proxy settings directly in actor input for more reliable collection.

Use Cases

Competitive Price Monitoring

Track current and original prices across product categories to detect discount cycles and competitor positioning. Use recurring runs to observe pricing movement over time.

Product Assortment Analysis

Build structured datasets of Houzz listings to compare brand coverage, product types, and category depth. This helps identify assortment gaps and expansion opportunities.

Trend and Demand Research

Use keyword-based searches to collect product signals for seasonal planning and merchandising decisions. Ratings and review volumes can highlight high-interest product groups.

Interior Design Sourcing

Create a research dataset of furniture and decor options with direct product URLs for quick review. This supports mood boards, shortlist creation, and client-facing recommendations.

Data Pipelines and BI Reporting

Export structured output into analytics tools for dashboards, benchmarks, and historical comparisons. Teams can combine this dataset with internal sales data for richer insights.

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Input Parameters

Parameter	Type	Required	Default	Description
query	String	No	"sofa"	Search phrase used to find products on Houzz.
results_wanted	Integer	No	20	Maximum number of products to collect.
max_pages	Integer	No	20	Safety cap for how many result pages are processed.
proxyConfiguration	Object	No	{"useApifyProxy": false}	Proxy settings for your run.

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Output Data

Each dataset item contains:

Field	Type	Description
title	String | null	Product title.
brand	String | null	Manufacturer or vendor name.
price	String | null	Current product price, formatted as currency.
original_price	String | null	Original price when a discount is detected.
on_sale	Boolean	true when the product is currently on sale.
image_url	String | null	Main product image URL.
rating	Number | null	Average rating value when available.
review_count	Integer | null	Number of customer reviews when available.
description	String | null	Product description when available from source data.
specifications	String | null	Product materials/specification text when available.
url	String	Direct product URL.
sku	String | null	Product identifier when available.
product_type	String | null	Product style/type classification when available.

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Usage Examples

Basic Product Extraction

Collect a quick sample for validation:

{
  "query": "sofa",
  "results_wanted": 30,
  "max_pages": 3
}

Broader Category Collection

Gather a larger dataset for analysis:

{
  "query": "outdoor patio furniture",
  "results_wanted": 250,
  "max_pages": 12
}

Reliability-Focused Run with Proxies

Use proxy settings for stable high-volume collection:

{
  "query": "dining table",
  "results_wanted": 150,
  "max_pages": 8,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

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Sample Output

{
  "title": "Modern Linen Sectional Sofa",
  "brand": "Everline Home",
  "price": "$1299.00",
  "original_price": "$1599.00",
  "on_sale": true,
  "image_url": "https://st.hzcdn.com/fimgs/example-product.jpg",
  "rating": 4.6,
  "review_count": 87,
  "description": null,
  "specifications": "Engineered wood frame, linen upholstery, foam cushions",
  "url": "https://shophouzz.com/products/modern-linen-sectional-sofa",
  "sku": "HZ-SECTIONAL-88421",
  "product_type": "Modern"
}

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Tips for Best Results

Choose Focused Search Queries

• Use specific phrases like mid century coffee table instead of broad terms like table.
• Run separate jobs per category to keep datasets clean and comparable.

Balance Depth and Speed

• Start with results_wanted between 20 and 100 to validate output quality.
• Increase max_pages only when you need larger datasets.

Plan Large Collections in Batches

• Split high-volume collection into multiple keyword runs.
• Merge results later in your BI tool or warehouse for easier analysis.

Expect Natural Field Gaps

• Some products may not expose ratings, reviews, or brand details.
• Treat nullable fields as normal when building downstream pipelines.

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Proxy Configuration

For more reliable collection, use Apify Proxy:

{
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

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Integrations

Connect your dataset with:

• Google Sheets — Share product research with non-technical teams.
• Airtable — Build searchable product databases and workflows.
• Looker Studio — Create visual dashboards for trend monitoring.
• Make — Automate downstream enrichment and notifications.
• Zapier — Trigger actions in your internal tools.
• Webhooks — Send run results directly to custom endpoints.

Export Formats

• JSON — Best for APIs and engineering workflows.
• CSV — Easy spreadsheet analysis and reporting.
• Excel — Business-ready handoff format.
• XML — Compatible with legacy systems and connectors.

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Frequently Asked Questions

How many products can I collect in one run?

You can collect as many as available for your query. Use results_wanted and max_pages to control runtime and volume.

Can I scrape multiple pages of results?

Yes. The actor iterates through result pages until your limits are reached or no more products are found.

Why are some fields empty?

Some listings do not expose every field. Null values are expected for optional data such as ratings, descriptions, or SKU.

Does the actor reduce duplicates?

Yes. Duplicate product URLs are filtered so your dataset is cleaner for analysis.

Can I schedule this actor to run automatically?

Yes. Use Apify schedules to run daily, weekly, or custom intervals.

Can I export the data to spreadsheets or BI tools?

Yes. Apify datasets can be exported in multiple formats and connected to common automation and analytics tools.

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Support

For issues or feature requests, contact support through the Apify Console.

Resources

• Apify Documentation
• Apify API Reference
• Apify Scheduling

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Legal Notice

This actor is intended for legitimate data collection use cases. You are responsible for complying with website terms, local laws, and platform policies when collecting and using data.