IKEA Reviews + Stats Scraper

This Actor scrapes customer reviews and rating statistics from a single IKEA product page and returns the data in a clean JSON format.

The scraper is designed to be simple to use:

• You give it a product URL and maximum number of reviews.
• It returns one JSON object per review, including both review details and product-level rating stats.

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1. Typical use cases

• Analyzing customer sentiment for a specific IKEA product.
• Building dashboards of product ratings and review volume.
• Comparing rating distributions between different variants or markets.
• Detecting potential product issues from low-rating spikes.

2. What this scraper does

For a given IKEA product URL, the scraper will:

1. Open the product page and load the reviews section.
2. Collect up to maxreviews reviews (or fewer, if not enough exist).
3. For each review, extract:
   • Review text
   • Star rating
   • Reviewer name or anonymous flag
   • Review date
   • Verification flags (verified purchase, verified reviewer)
4. Attach product-level statistics to every review record:
   • Average rating
   • Total number of reviews
   • Rating breakdown (1 to 5 stars)
   • First review date
5. Return everything as structured JSON.

This makes the result easy to use in scripts, dashboards, or analysis tools.

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3. Input

The scraper expects a JSON configuration with two required fields: URL and maxreviews.

3.1 Input parameters

• URL (string, required)
  Full IKEA product URL to scrape reviews from.
  Example:
  https://www.ikea.com/in/en/p/ekoln-soap-dispenser-beige-30493005/

• maxreviews (integer, required)
  Maximum number of reviews to collect for this product. The scraper will stop once this limit is reached or there are no more reviews available.
  Default: 500

3.2 Example input

{
  "URL": "https://www.ikea.com/in/en/p/ekoln-soap-dispenser-beige-30493005/",
  "maxreviews": 300
}

---

4. Output

The scraper returns one JSON object per review.
Each object contains:

• Product identifiers and context
• Review content and metadata
• Verification flags
• Product-level rating statistics

4.1 Sample output record

{
  "itemNo": "30493005",
  "URL": "https://www.ikea.com/in/en/p/ekoln-soap-dispenser-beige-30493005/",
  "sourceCountryCode": "us",
  "Title": "Soap dispenser,",
  "Review": "Great color and good size , works well, easy to use , but it is a soap dispenser, your not doing brain surgery with it",
  "Rating": 5,
  "verifiedPurchase": true,
  "verifiedReviewer": false,
  "anonymousReviewer": false,
  "Review Date": "2025-11-09",
  "Username": "Janet",
  "Date of Crawling": "2025-11-15",
  "Average Rating": 4.4,
  "Global Rating Count": 1270,
  "firstReviewedOn": "2019-07-14",
  "Count_1_star": 78,
  "Count_2_star": 49,
  "Count_3_star": 79,
  "Count_4_star": 208,
  "Count_5_star": 856
}

4.2 Field description

Product and context

• itemNo (string)
  IKEA product/item number.

• URL (string)
  Product page URL that was scraped.

• sourceCountryCode (string)
  Country/locale code of the IKEA site (for example: us, in, de).

• Title (string)
  Product name or title shown on the IKEA product page.

Review details

• Review (string)
  The full text of the customer review.

• Rating (number)
  Star rating given by the reviewer, usually from 1 to 5.

• verifiedPurchase (boolean)
  true if the review is marked as a verified purchase.

• verifiedReviewer (boolean)
  true if the reviewer’s identity is verified (depending on what IKEA exposes).

• anonymousReviewer (boolean)
  true if the review is posted anonymously.

• Review Date (string, YYYY-MM-DD)
  The date when the review was posted.

• Username (string)
  Display name of the reviewer (or a generic/anonymous name, depending on what is shown on the site).

Crawling metadata

• Date of Crawling (string, YYYY-MM-DD)
  The date when this review was collected by the scraper.
  Useful for tracking data freshness and incremental updates.

Product-level rating statistics

These fields describe the overall rating situation for the product at the time of crawling.
They are repeated for every review record so that each record is self-contained.

• Average Rating (number)
  Overall average rating for the product.

• Global Rating Count (integer)
  Total number of reviews for this product.

• firstReviewedOn (string, YYYY-MM-DD)
  Date of the earliest review found for this product.

• Count_1_star (integer)
  Number of 1-star reviews.

• Count_2_star (integer)
  Number of 2-star reviews.

• Count_3_star (integer)
  Number of 3-star reviews.

• Count_4_star (integer)
  Number of 4-star reviews.

• Count_5_star (integer)
  Number of 5-star reviews.

---

5. Output file formats

Depending on how you run the scraper, the results may be saved as:

5.1 JSON array

A single file containing an array of review objects:

[
  { "itemNo": "30493005", "Review": "Nice product", "Rating": 5 },
  { "itemNo": "30493005", "Review": "Okay for the price", "Rating": 3 },
  { "itemNo": "30493005", "Review": "Not happy", "Rating": 2 }
]

5.2 NDJSON / JSON Lines

One JSON object per line, which works well for streaming and big data tools:

{"itemNo": "30493005", "Review": "Nice product", "Rating": 5}
{"itemNo": "30493005", "Review": "Okay for the price", "Rating": 3}
{"itemNo": "30493005", "Review": "Not happy", "Rating": 2}

Both formats contain the same information. Choose the one that fits your tooling better.

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6. Quick summary

• You provide:

  • URL: IKEA product page
  • maxreviews: how many reviews you want at most

• You get:

  • One JSON object per review
  • Clean fields for text, rating, reviewer, and dates
  • Product-level rating statistics included with each review

This README is meant to give you everything you need to understand the input and output format and to plug the scraper into your own pipelines.