Home Depot Product Reviews Scraper | Extract Customer Ratings & Feedback (US)

Scrape Home Depot reviews, ratings, photos, and seller responses from any Home Depot US product page — clean, analysis-ready data for sentiment analysis, competitor research, and e-commerce analytics.

Paste a product URL → choose Max Mode (maximize unique coverage) or filters → get structured results you can export as JSON, CSV, or Excel.

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60-second overview

Goal	What to set
Max coverage	maxMode = true
Quick sample (e.g. latest 30)	maxMode = false, sort newest, maxreviews = 30
Only 1★ complaints	maxMode = false, starRatings = ["1"]
Broad coverage without Max Mode	Select all sorts × star ratings 1–5 (see below)

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Why use this Home Depot review scraper?

• Max Mode — maximizes unique coverage; often the full set for typical products. High-volume SKUs may be partial due to site limits.
• Rich fields — stars, review text, photos, verified purchase, incentivized flags, seller replies, helpful votes, and rating breakdowns.
• Analysis-ready output — product stats (Average_Rating, Total_Reviews, star counts) included on every row.
• Flexible filters — newest / oldest / photos / most helpful / highest / lowest × 1–5 stars.
• Easy exports — run on Apify, push to Dataset, download CSV/Excel/JSON for dashboards (Power BI, Looker, Sheets) or Python.

Ideal for: product managers, brand analysts, market research, VOC / voice-of-customer, assortment teams, and AI/NLP pipelines.

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Max Mode — maximize unique coverage

Turn maxMode ON when you want the broadest unique review set for a product.

Max Mode maximizes unique coverage — often the full set for typical products. High-volume SKUs may be partial due to site limits.

While Max Mode is ON, sort and star filters are ignored — the actor focuses on maximizing coverage automatically.

{
  "URL": "https://www.homedepot.com/p/PRODUCT-NAME/317525930",
  "maxMode": true,
  "maxreviews": 5000
}

Tip: keep maxreviews high (e.g. 5000) so the run does not stop early.

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Filters (Max Mode OFF)

When maxMode = false, you control exactly what is collected using sort × star combinations.

Available sorts

Input value	Meaning
newest	Most recent reviews
oldest	Oldest first
photoreview	Reviews with photos
mosthelpfull	Most helpful
highestrating	Highest star first
lowestrating	Lowest star first

Star ratings

all · 5 · 4 · 3 · 2 · 1

Examples

Latest reviews only:

{
  "URL": "https://www.homedepot.com/p/.../317525930",
  "maxMode": false,
  "sorts": ["newest"],
  "starRatings": ["all"],
  "maxreviews": 100
}

Only negative feedback (1–2 stars):

{
  "URL": "https://www.homedepot.com/p/.../317525930",
  "maxMode": false,
  "sorts": ["newest"],
  "starRatings": ["1", "2"],
  "maxreviews": 2000
}

Photo reviews + most helpful:

{
  "URL": "https://www.homedepot.com/p/.../317525930",
  "maxMode": false,
  "sorts": ["photoreview", "mosthelpfull"],
  "starRatings": ["all"],
  "maxreviews": 2000
}

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Get broad / near-complete coverage without Max Mode

You can still aim for wide coverage with filters alone:

1. Set maxMode to false
2. Select all 6 sorts
3. Select stars 5, 4, 3, 2, 1 (or all)
4. Set maxreviews high enough

{
  "URL": "https://www.homedepot.com/p/.../317525930",
  "maxMode": false,
  "sorts": ["newest", "oldest", "photoreview", "mosthelpfull", "highestrating", "lowestrating"],
  "starRatings": ["5", "4", "3", "2", "1"],
  "maxreviews": 5000
}

Duplicates are removed automatically. For the broadest pull with the least setup, Max Mode is the simplest choice.

Approach	Best for
Max Mode ON	Maximize unique coverage / VOC dumps / model training
Filters (Max Mode OFF)	Targeted pulls — complaints, photos, latest only

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Input reference

Field	Required	Description
URL	Yes	Home Depot US product URL (must include the numeric item id)
maxMode	No (default true)	true = maximize unique coverage; false = use sort/star filters
sorts	No	Multi-select; used only when maxMode is false
starRatings	No	all or 1–5; used only when maxMode is false
maxreviews	No	Maximum unique reviews to keep (e.g. 30 for a quick test)

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Output — sample review object

Each dataset item is one review, with review details and product-level stats:

{
  "Review_ID": "400190853",
  "Title": "Bring my Bagged Wind Tunnel Back!!",
  "ReviewText": "Please bring back the bagged Windtunnel!...",
  "Rating": 1,
  "SubmissionDate": "2026-08-11",
  "LastModificationDate": "2026-08-19",
  "UserNickname": "Neen",
  "UserLocation": "Fort Myers FL",
  "AuthorId": "zsq5y832cofhg9tswr7u0e5kvm",
  "ProductId": "317525930",
  "Item_ID": "317525930",
  "Product_URL": "https://www.homedepot.com/p/.../317525930",
  "IsRecommended": null,
  "IsRatingsOnly": false,
  "IsFeatured": false,
  "IsSyndicated": true,
  "SourceClient": "hoover-us",
  "ContentLocale": "en_US",
  "Helpfulness": 0,
  "TotalPositiveFeedbackCount": 0,
  "TotalNegativeFeedbackCount": 0,
  "TotalFeedbackCount": 0,
  "BadgesOrder": ["verifiedPurchaser"],
  "IsVerifiedPurchaser": true,
  "IncentivizedReview": false,
  "IncentivizedReview_Label": null,
  "PhotoCount": 1,
  "PhotoUrls": ["https://example.com/photo.jpg"],
  "HasSellerResponse": true,
  "SellerResponse_Department": "Hoover Customer Support",
  "SellerResponse_Date": "2026-08-19",
  "SellerResponse_Text": "Thank you for taking the time to share your feedback...",
  "Review_Type": "with_review_text",
  "With_Review": "Yes",
  "Sort": "newest",
  "Scrape_Pass": "newest_all_stars",
  "Total_Reviews": 1348,
  "Average_Rating": 4.21,
  "Product_RatingsOnlyReviewCount": 506,
  "Product_RecommendedCount": 980,
  "Product_NotRecommendedCount": 120,
  "Product_5_Star_Count": 430,
  "Product_4_Star_Count": 172,
  "Product_3_Star_Count": 78,
  "Product_2_Star_Count": 64,
  "Product_1_Star_Count": 89
}

Download from the Apify Dataset as JSON / CSV / Excel.

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What analysis can you run on this data?

1. Rating & quality monitoring

• Track Average_Rating and star mix (Product_1_Star_Count … Product_5_Star_Count)
• Spot rating changes after product updates or new listings

2. Sentiment & text mining

• Run sentiment on ReviewText / Title
• Find common complaints vs praise themes
• Compare language in 1–2★ vs 4–5★ reviews

3. Trust & authenticity signals

• Filter IsVerifiedPurchaser, IncentivizedReview, IsSyndicated
• Separate rating-only rows (Review_Type) from written reviews

4. Photo & UGC research

• Use PhotoCount / PhotoUrls for visual customer content

5. Brand response quality

• Measure reply rate with HasSellerResponse
• Compare SubmissionDate vs SellerResponse_Date

6. Competitor & assortment research

• Run multiple Home Depot product URLs
• Benchmark volume, average rating, and negative-review share across brands

7. Trends over time

• Chart review volume by SubmissionDate
• Detect launch spikes or seasonal patterns

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Tips

• Prefer Max Mode when you want maximum unique coverage (full set for typical products; high-volume SKUs may be partial due to site limits).
• Use filters + a small maxreviews for cheap tests or “latest only” dashboards.
• One URL = one product; run multiple times (or a workflow) for category research.
• Some fields may be empty when the site does not provide them (e.g. location, recommend flag) — that is normal.

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Keywords

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Built for teams who need reliable Home Depot US review data — without manual copy-paste.