Wayfair Scraper — Products, Prices & AI Reviews API — No API Key 🛋️

🎉 Scrape Wayfair products, prices, and reviews — with an AI review summary no other Wayfair scraper gives you — no API key, no approval, no developer account

Built for price-tracking SaaS founders, e-commerce ops teams, furniture & home-goods researchers, and merchandising analysts who need clean Wayfair.com data on a schedule

📋 Overview

Wayfair data extraction made ridiculously simple. Point this actor at a search term, a brand, or a single product SKU — click Run — and get clean, query-ready rows back. No login, no proxy setup, and no waiting on a Wayfair API key or developer approval. It's the Wayfair data API you can actually use today.

Most Wayfair scrapers on the Store do one thing — search or product details — and brittle browser scrapers get blocked the moment Wayfair's anti-bot kicks in. This actor bundles three operations behind a single dropdown: keyword (or whole-brand) product search, deep product details, and paginated customer reviews — uniquely surfacing Wayfair's AI-generated review summary and aspect sentiments on every review row. Pick one operation per run, get one tidy dataset out. Perfect for building a Wayfair price tracker, mapping competitor catalogs, and mining voice-of-customer review insights without running your own NLP.

Why professionals choose us:

• ✅ Wayfair API alternative, zero setup: no API key, no developer registration — paste an input and run
• 🤖 AI review intelligence — a SIÁN exclusive: every review row carries Wayfair's AI-generated review summary and aspect sentiments. No other Wayfair (or cross-platform) review scraper exposes this
• 🛡️ Reliable where rivals get blocked: Wayfair actively blocks direct scraping. Our upstream absorbs the anti-bot layer and we retry transparently — you get data, not "Blocked" errors
• 💰 Built for price tracking: capture price, listPrice, isOnSale, and stock status on a schedule, then diff the dataset to catch price moves
• ⚡ 3 operations in one actor: product search · product details · reviews + AI summary
• 💎 Pay only for successful rows: failed lookups land as status:"error" rows at zero cost — you're never billed for a hiccup

✨ Features

• 🔍 Product Search: keyword search OR whole-brand browse (by manufacturer ID) across Wayfair.com, paginated (up to 96 products/page) with sort, color, and price filters
• 📦 Product Details: deep single-product scrape by SKU — price, specs, images, rating, brand, and full description
• ⭐ Product Reviews + AI Summary: paginated customer reviews (text, rating, author, verified-purchase) plus Wayfair's AI review summary and aspect sentiments attached to every row
• 💲 Price & Stock Capture: price, listPrice, isOnSale, promoText, and inStock on every product row — ready for a price-tracking pipeline
• 🏷️ Brand & Category Browse: list an entire brand by manufacturer ID, optionally narrowed to a category ID — for share-of-shelf and assortment analysis
• 🌍 5 marketplaces: query wayfair.com (US), .ca, .co.uk, .ie, or .de with one setting per run
• ↕️ Native Sort & Filter: recommended, customer rating, price low/high — plus color, min/max price, and in-stock-only filters
• 🖼️ HTTPS-Normalized URLs: every product image and link arrives ready to embed
• 📊 Single Clean Dataset Shape: one flat row per item, filterable by _operation and status — same export pipeline across all three operations

🎬 Quick Start

So simple, no training needed! Pick an operation, fill the matching input, click Run.

# Or use the API — one line
curl -X POST https://api.apify.com/v2/acts/sian.agency~wayfair-data-scraper/runs?token=YOUR_TOKEN \
-d '{"operation":"search","query":"sofa","sortBy":"recommended","maxPages":3}'

🚀 Getting Started (3 Simple Steps)

Step 1: Pick an Operation

Choose one of three operations from the dropdown: Product Search, Product Details, or Product Reviews. One run = one operation.

Step 2: Fill the Matching Input

• Search → a query (e.g. sofa) or a manufacturerId to browse a whole brand
• Product Details / Reviews → a sku (e.g. W110469263)

Optionally set domain (com / ca / co.uk / ie / de), sortBy, itemsPerPage, color/price filters, and maxPages.

Step 3: Click Run

One click and we scrape, flatten, normalize, and push clean rows to your dataset. An HTML run report lands in the key-value store. Export to JSON, CSV, or Excel from the Apify console — or pull via API.

That's it! In seconds, you'll have:

• Clean flat rows from any of three Wayfair endpoints — same shape, ready to export
• Curated camelCase fields per row plus raw upstream data spread alongside
• Price, list price, sale flag, rating, and stock status on every product row
• Review rows enriched with the AI summary and aspect sentiments
• HTTPS image and product URLs ready to embed
• Error rows for failed inputs — never billed

📥 Input Configuration

One operation per run. Each operation has its own required field (validated before charging). The optional domain and pagination/filter fields apply where relevant.

Field	Type	Required	Description
operation	enum	Yes	One of: search, productDetails, productReviews
query	string	search*	Keyword to search Wayfair (e.g. sofa)
manufacturerId	string	search*	Brand/manufacturer ID to browse a whole brand (alternative to query)
sku	string	productDetails, productReviews	Wayfair product SKU (e.g. W110469263)
domain	enum	No	com (default), ca, co.uk, ie, de
sortBy	enum	No (search)	recommended, customer_rating, price_low_to_high, price_high_to_low
itemsPerPage	enum	No (search)	24, 48 (default), 96 results/page
categoryId	string	No (search)	Narrow search to a Wayfair category ID
color	string	No (search)	Color filter (e.g. Black, Blue)
minPrice / maxPrice	integer	No (search)	Price filters (USD)
inStock	boolean	No (search)	Return only in-stock products
reviewSort	enum	No (reviews)	relevance, helpful, date_descending, date_ascending, rating_descending, rating_ascending
reviewStar	enum	No (reviews)	Return only reviews with this star rating (1–5); blank = all
maxPages	integer	No	1–50, controls paginated runs (default 5)

* Search requires either query or manufacturerId.

Example — Product Search:

{
  "operation": "search",
  "query": "sofa",
  "sortBy": "customer_rating",
  "itemsPerPage": "48",
  "maxPages": 3
}

Example — Brand Browse (whole manufacturer):

{
  "operation": "search",
  "manufacturerId": "YOUR_BRAND_ID",
  "maxPages": 5
}

Example — Product Details (single product):

{
  "operation": "productDetails",
  "sku": "W110469263"
}

Example — Product Reviews + AI Summary (newest first):

{
  "operation": "productReviews",
  "sku": "W110469263",
  "reviewSort": "date_descending",
  "maxPages": 5
}

💡 Workflow tip: Run Search to discover SKUs, then loop Details / Reviews per product.

📤 Output

One flat row per item, saved to the Apify dataset. Search rows carry product fields; details rows carry the full product; review rows carry review fields plus the AI summary and aspect sentiments. Curated camelCase aliases land on every row alongside the raw upstream data. Filter by _operation to split modes, or by status to separate success from error rows.

Field	Type	Description
sku	string	Wayfair product SKU
productName	string	Product display name
brand	string	Brand / manufacturer
price / listPrice	number	Current price and list price
priceDisplay / currency	string	Formatted price and currency
isOnSale / promoText	boolean / string	Sale flag and promo text
rating / reviewCount	number / integer	Average rating and review count
inStock / freeShipping	boolean	Stock and shipping flags
shippingText / deliveryEstimate	string	Shipping and delivery info
descriptionSnippet / productDescription	string	Product description
categories / specifications / variants	array	Breadcrumbs, specs, variant options
image / images / productUrl	string / array	HTTPS image gallery and product URL
reviewId / reviewBody / reviewRating / verifiedPurchase	string / number / boolean	Review fields (Product Reviews)
aiReviewSummary	string	🤖 Wayfair's AI-generated review summary (Product Reviews)
aspectSentiments	array	🤖 Aspect-level sentiment breakdown — [{name, count, sentiment}] (Product Reviews)
_operation / _fetchedAt / _page / status	metadata	Always-present row metadata

Example — Product Search row:

{
  "_operation": "search",
  "sku": "W110469263",
  "productName": "Wide Reversible Sofa & Chaise with Ottoman",
  "brand": "Latitude Run",
  "price": 549.99,
  "listPrice": 899.99,
  "isOnSale": true,
  "rating": 4.5,
  "reviewCount": 1283,
  "inStock": true,
  "freeShipping": true,
  "productUrl": "https://www.wayfair.com/furniture/pdp/...html",
  "status": "success"
}

Example — Product Review row (with AI summary):

{
  "_operation": "productReviews",
  "sku": "W110469263",
  "reviewId": 123456789,
  "reviewBody": "Assembly took 20 minutes and the cushions are firm but cozy...",
  "reviewRating": 5,
  "reviewDate": "2026-01-12",
  "reviewAuthor": "Jamie",
  "reviewerLocation": "Austin, TX",
  "verifiedPurchase": true,
  "aiReviewSummary": "Customers praise comfort and value; some note firm cushions and a longer assembly.",
  "aspectSentiments": [
    { "name": "Comfort", "count": 312, "sentiment": "positive" },
    { "name": "Value", "count": 188, "sentiment": "positive" },
    { "name": "Assembly", "count": 47, "sentiment": "mixed" }
  ],
  "status": "success"
}

Example rows mirror the upstream response schema (field names are stable). Wayfair actively blocks direct scraping; this actor retries transparently to return live data.

💼 Use Cases & Examples

1. Price-Tracking SaaS — Build a Wayfair Price Tracker

For SaaS founders building a Wayfair price tracker without waiting on official API access.

Input: Schedule productDetails (or search) across your watched SKUs on a daily cron Output: price, listPrice, priceDisplay, isOnSale, and inStock per product, per run Use: Diff consecutive datasets to detect price drops and restocks — power "price dropped" alerts and historical price charts.

2. E-commerce Ops — Competitor Catalog & Brand Mapping

For e-commerce ops teams tracking competitor SKUs and pricing on Wayfair.com.

Input: Run search with a manufacturerId (whole-brand browse) or categoryId weekly Output: Full brand/category listings with prices, ratings, and sale flags (up to 96/page) Use: Map competitor assortment, catch new SKU launches, and benchmark price points across your segment.

3. AI Review Intelligence — Voice-of-Customer Without NLP

For brand and product teams mining Wayfair review sentiment at scale.

Input: productReviews paginated across competitor SKUs Output: Reviews with full text, rating, and verified-purchase flag — plus Wayfair's AI summary and aspect sentiments on every row Use: Surface complaints, feature requests, and competitor weaknesses instantly. No other Wayfair scraper hands you the AI summary — skip building your own sentiment pipeline.

4. Catalog Enrichment — Specs, Images & Descriptions

For teams building or enriching a furniture/home-goods product database.

Input: productDetails on a list of SKUs Output: Specs, variants, brand, full description, and HTTPS image gallery Use: Enrich your own catalog with structured, query-ready rows, or build a competitive product database with images ready to embed.

5. Merchandising Research — Ranking, Ratings & Sentiment

For merchandising analysts benchmarking listings against Wayfair best-sellers.

Input: search (sorted by customer_rating) + productReviews on top results Output: Search ranking and ratings combined with review sentiment Use: Quantify where rivals win or lose on price, delivery, and satisfaction for client-ready reports.

🔌 Integration Examples

JavaScript/Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });

// Discover SKUs, then enrich them
const search = await client.actor('sian.agency/wayfair-data-scraper').call({
  operation: 'search',
  query: 'sofa',
  maxPages: 2
});

const { items } = await client.dataset(search.defaultDatasetId).listItems();
const skus = items.filter(i => i.status === 'success').map(i => i.sku);
console.log(`${skus.length} SKUs to enrich`);

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')

# Pull reviews with the AI summary for a watched product
run = client.actor('sian.agency/wayfair-data-scraper').call(
    run_input={'operation': 'productReviews', 'sku': 'W110469263', 'maxPages': 3}
)

for item in client.dataset(run['defaultDatasetId']).iterate_items():
    if item.get('status') == 'success' and item.get('aiReviewSummary'):
        print('AI summary:', item['aiReviewSummary'])
        break

cURL

curl -X POST 'https://api.apify.com/v2/acts/sian.agency~wayfair-data-scraper/runs?token=YOUR_TOKEN' \
-H 'Content-Type: application/json' \
-d '{"operation":"productDetails","sku":"W110469263"}'

Automation Workflows (N8N / Zapier / Make)

1. Trigger: Schedule (daily price refresh) or webhook (new SKU added to your tracker)
2. HTTP Request: Call the actor API with operation and the per-op input fields
3. Process: Diff against yesterday's price, or score review sentiment from aiReviewSummary
4. Action: Push price-drop alerts to Slack, sync rows to Google Sheets, or update your price-tracking database

📈 Performance & Pricing

Transparent pay-per-event — you're charged only for successful rows, plus a small one-time start fee per run. Failed lookups land as status:"error" rows and cost $0. Higher Apify plans get automatic volume discounts on every event.

Event	Price	Applies to
apify-actor-start	$0.001	One-time per run
🔍 search-result	$0.0018 / row	Product Search
📦 product-detail-result	$0.012 / product	Product Details
⭐ product-review-result	$0.0035 / review	Product Reviews (incl. AI summary + aspect sentiments)

Cost examples:

• 1,000 search results → $1.80 + $0.001 start = ~$1.80
• A full product detail lookup → $0.012 + $0.001 = ~$0.01
• 1,000 customer reviews (with AI insights) → $3.50 + $0.001 = ~$3.50

💰 Bulk search is priced at a fraction of a cent per row — cheaper than maintaining your own proxies and parsers, with no Wayfair API approval to wait on.

🔗 View current pricing

❓ Frequently Asked Questions

Q: Does Wayfair have an API? A: Wayfair has no open public product API for search, full product details, or customer reviews. This actor is the practical Wayfair API alternative — it returns clean JSON for all of those, with no approval process.

Q: How do I get a Wayfair API key? A: You don't need one. This actor requires no Wayfair API key and no developer registration — just an Apify token. Paste your input, click Run, get structured data back.

Q: What makes the reviews operation different from other Wayfair scrapers? A: Every review row carries Wayfair's AI-generated review summary and aspect sentiments (e.g. comfort, value, assembly) alongside the raw reviews. No other Wayfair review scraper on the Store surfaces this — you get voice-of-customer insight without building your own NLP pipeline.

Q: Wayfair blocks scrapers — will this actually return data? A: Wayfair actively blocks direct scraping, which is why brittle browser scrapers often fail. This actor's upstream absorbs the anti-bot layer and the actor retries transparently on transient blocks, so you get data instead of "Blocked" errors. Persistent block windows surface as status:"error" rows at $0 — just re-run.

Q: Can I use this as a Wayfair price tracker? A: Yes — that's a core use case. Schedule productDetails or search on a cron and diff the dataset run-to-run to capture price drops, sales (isOnSale), and restocks. Every product row carries price, listPrice, and inStock.

Q: How do I browse a whole brand instead of searching keywords? A: Use the Search operation with a manufacturerId instead of a query. Optionally add a categoryId to narrow a brand to one category.

Q: Which marketplaces are supported? A: US (wayfair.com, domain: "com"), Canada (ca), UK (co.uk), Ireland (ie), and Germany (de). One setting per run.

Q: Where do I find a product SKU? A: SKUs (e.g. W110469263, MBYC1062) appear in every Product Search result row (the sku field) and in Wayfair product URLs.

Q: What output formats are available? A: JSON, CSV, and Excel — export directly from the Apify dataset console, or pull via API.

Q: How am I billed, and what about failed lookups? A: Pay-per-event — only successful rows are charged, plus a one-time start fee. Failed lookups land as status:"error" rows at $0.

🐛 Troubleshooting

A run returns status:"error" with "temporarily unavailable"

• Wayfair hit a transient block or the data source had a hiccup. The actor retries automatically with backoff. Re-run after a moment — error rows are never charged.

Paginated runs stop early before maxPages

• The actor stops pagination when the data source reports the last page (total_pages). This is correct behavior, not a bug — you're not billed for empty pages.

Product Details / Reviews returns "not found"

• Confirm the sku. It must be the Wayfair SKU (e.g. W110469263), which appears in any Search row and in product URLs.

Search returns fewer rows than expected

• Thin coverage for a query returns fewer than itemsPerPage rows. Broaden the query, relax minPrice/maxPrice/color, or paginate deeper with maxPages. Try itemsPerPage: "96" for more per call.

Brand browse returns nothing

• Confirm the manufacturerId. Brand IDs appear in Wayfair brand-page URLs. Provide either a query or a manufacturerId for Search — not neither.

🧰 More by SIÁN Agency

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• Sephora Product Details & Reviews Scraper — beauty products, ratings & reviews
• Browse all SIÁN actors →

🤝 Support

Join our active support community

• For issues or feature requests, open an issue in the actor's repository or use the Issues tab on the actor page
• Check SIÁN Agency Store for more automation tools
• 📧 apify@sian-agency.online
• ⭐ If this saves you time, a 5-star review helps us ship more features.

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⚠️ Trademark Disclaimer

This actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Wayfair Inc. "Wayfair" and related marks are trademarks of their respective owners and are used here only to describe the data this tool helps you collect. Use this actor responsibly and in compliance with applicable laws, Wayfair's terms of service, and data-protection regulations (including GDPR and CCPA where applicable). You are responsible for how you use the data you extract.

Legal

Scrape only publicly available data and use it lawfully. For guidance on ethical and compliant web scraping, see Apify's guide to web scraping legality. Do not collect personal data in violation of GDPR, CCPA, or other applicable privacy laws.

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