We extract home product listings, pricing, professional directory profiles, project portfolio images, ideabook save counts, and review corpora from Houzz. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Listings objects from houzz.com. All fields typed and schema-versioned.
"product_id": "hz_prod_9384712", "title": "Hendrix Mid-Century Modern Sofa — Walnut & Fog Grey", "brand": "Article", "price": 1299.00, "currency": "USD", "ideabook_saves": 8412, "style_tags": ["Mid-Century Modern", "Scandinavian"], "room_tags": ["Living Room"], "rating": 4.7, "review_count": 1284
| # | product_id | title | brand | vendor | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pro Directory objects from houzz.com. All fields typed and schema-versioned.
"pro_id": "hz_pro_291847", "business_name": "Meridian Interior Design Studio", "pro_type": "Interior Designer", "location_city": "Austin", "location_state": "TX", "rating": 4.9, "review_count": 84, "houzz_badge": "BEST_OF_HOUZZ", "license_verified": true, "typical_job_cost_min": 50000
| # | pro_id | business_name | pro_type | location_city | location_state | location_country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from houzz.com. All fields typed and schema-versioned.
"review_id": "hz_rv_48291034", "target_type": "PRO", "star_rating": 5, "review_title": "Full kitchen renovation — exceeded every expectation", "project_type": "Kitchen Remodel", "project_cost_range": "$50,000–$100,000", "verified_hire": true, "helpful_votes": 31, "review_date": "2026-03-18"
| # | review_id | target_type | target_id | reviewer_name | star_rating | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search & Ideabooks objects from houzz.com. All fields typed and schema-versioned.
"query": "mid century modern sofa", "result_type": "PRODUCT", "position": 3, "product_or_pro_id": "hz_prod_9384712", "ideabook_saves": 8412, "is_sponsored": false, "style_tags": ["Mid-Century Modern"], "scraped_at": "2026-05-12T08:15:00Z"
| # | query | result_type | position | product_or_pro_id | title | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Houzz is uniquely dual-sided: a home products marketplace and an interior design professional directory. Our scraper covers both — product listings with ideabook signals, pro profiles with verification status, project portfolios, and the full review corpus.
Title, brand, vendor, dimensions, materials, colour options, style and room tags, ideabook saves, and pricing — the full product record at listing level.
Capture ideabook save counts per product and photo — Houzz's unique demand-proxy metric, indicating consumer aspiration and intent at scale.
Pro type, location, rating, review count, Best of Houzz badge, years in business, typical job cost range, service areas, and licence verification status — per professional.
Pro project titles, style tags, room types, photo counts, and ideabook saves per project — the portfolio intelligence that drives homeowner hiring decisions.
Full review text, star ratings, project type, cost range, verified hire flag, and helpful votes — for both product and professional reviews.
Houzz's granular style tags (Mid-Century, Farmhouse, Japandi) and room tags extracted per product and project — enabling style-trend analysis at catalogue scale.
Track organic vs sponsored product and pro placements for any keyword — capturing Houzz's mixed product/photo/pro search result format.
Pro directory data by city, state, and service area — enabling geographic coverage maps for pro supply density analysis.
One-off catalogue or directory exports, or continuous pipelines at daily or weekly cadences with change-detection diffing.
Brief in. Clean data out.
Specify product categories, pro types, geographic markets, or keyword sets. We design the extraction schema for products, pros, or both together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for houzz.com.
Ideabook save null-rate audits, pro rating completeness checks, review verification flag validation, and sample records before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Houzz's dual product-and-pro structure, infinite scroll photo feeds, and ideabook signal extraction require specialised parsing beyond standard e-commerce scraping.
Houzz search results interleave products, project photos, and professional listings within the same SERP. Our parser correctly classifies and routes each entity type — extracting product fields, pro fields, and photo fields to separate schema-validated tables from a single crawl.
Ideabook save counts are Houzz's equivalent of Etsy favourites — a public signal of consumer aspiration and product desire not available via API. We scrape save counts per product and per project photo, enabling save-velocity analysis and trending style detection.
Houzz photo feeds, ideabooks, and pro project galleries load via infinite scroll. Our Playwright pipeline triggers scroll events to load full content before extraction — capturing the complete dataset rather than just the above-the-fold subset.
Houzz surfaces licence verification and background check status for professionals. Our pipeline extracts these trust signals per pro record — valuable for building homeowner-facing trust rankings and professional market quality assessments.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, ideabook save outliers, pro rating coverage drops, and schema drift — and respond before you notice. SLA uptime is contractual, not aspirational.
Furniture brands and retailers use Houzz ideabook saves, style tags, and price points to identify trending aesthetics and demand for specific product categories before committing to new collections.
Home improvement platforms, contractor marketplaces, and insurance companies use Houzz professional directory data to map pro supply, quality distribution, and pricing by geography.
Design publications, trend forecasters, and FMCG brand teams use Houzz style tag and ideabook save data as a leading indicator of interior design trends — before they surface in mainstream retail.
ML teams use Houzz product descriptions, style tags, room tags, and project photos as training data for interior design AI — recommendation engines, style classifiers, and room-planning tools.
Economists, real estate analysts, and construction firms use Houzz pro review data — project types, cost ranges, verified hire frequency — as a proxy for home renovation activity and consumer spending.
Home goods brands track competitor product ideabook saves, style positioning, price tiers, and review velocity on Houzz to understand relative brand desirability and market positioning.
"Houzz's ideabook save count is the home industry's most honest signal of consumer aspiration — and its professional directory is the most comprehensive quality-rated contractor dataset in the US. Neither is queryable unless you build the pipeline."
Houzz's dual product-and-pro structure, infinite scroll feeds, and save-count signals require parsing logic that goes well beyond standard e-commerce scraping. DataFlirt absorbs that complexity so your design researchers, market analysts, and brand teams can focus on the trends — not the infrastructure.
Everything supported by our houzz.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles Houzz's React-rendered product pages, infinite scroll feeds, and professional profile tabs.
We maintain pools of US residential ISP proxies. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About houzz.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Houzz is generally permissible under applicable law — reinforced by the hiQ v. LinkedIn ruling and similar precedents. DataFlirt targets only public, non-authenticated product, professional, and review data. We do not extract personal contact details, circumvent authentication walls, or violate GDPR or applicable US privacy law. We recommend clients review Houzz's ToS independently and consult legal counsel for specific use cases.
Yes. Our pipeline handles both Houzz's product marketplace and its professional directory in a single engagement. Products, pro profiles, project portfolios, and reviews are extracted to separate schema-validated tables — so you can query them independently or join them on shared signals.
The ideabook save count is the number of times a product or project photo has been saved to a Houzz user's ideabook — a public signal of consumer aspiration and design intent. It's the home design equivalent of Etsy favourites, and it's not available via Houzz's API. For trend research and demand modelling, it's the most distinctive signal on the platform.
Yes. Houzz pros often publish typical job cost ranges (e.g. $25,000–$50,000) on their profiles. We extract minimum and maximum cost range values where available — useful for understanding service pricing distribution across markets and pro quality tiers.
Yes. Pro profiles include location city, state, and service area lists. We can deliver a geographically structured pro directory for any US state, metro area, or service region — enabling supply density analysis, coverage gap identification, and competitive mapping.
Our smallest packages start at a defined category or pro type and geography (typically 2,000–15,000 products or 1,000–5,000 pros) with weekly delivery. For full-catalogue or multi-market programmes, we price based on volume and cadence.
Yes. Every pipeline run captures timestamped ideabook save counts per product. Save velocity — the rate at which a product accumulates saves over time — is computable from the resulting time-series, and is available from the date your pipeline starts.
Absolutely. We provide a sample run of up to 300 products and 200 pro profiles as part of the pre-engagement scoping process — so you can validate schema fit, ideabook save completeness, and field coverage before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a home furnishings trend database, a pro directory map, or ideabook save velocity tracking across 500K products — we scope, build, and operate the pipeline. Tell us what you need.
