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Sears Reviews Scraper

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Sears Reviews Scraper

Sears Reviews Scraper

muhammetakkurtt/sears-reviews-scraper
Try for free

1 day trial then $19.99/month - No credit card required now

This Apify actor automatically collects customer reviews from Sears product pages. By entering the product URL, it obtains detailed review data such as title, comment, rating, user information and number of upvotes. The collected data is stored in a structured format in the Apify data store.

Sears Product Review Scraper

Sears Product Review Scraper

This project is an Apify actor designed to scrape product reviews from Sears. It collects detailed information about product reviews, including ratings, comments, and reviewer details.

Features

  • Fetches review data from specific Sears product URLs.
  • Collects information such as review ID, headline, comments, rating, and reviewer details.
  • Provides detailed data on review creation and update dates.
  • Offers information on review helpfulness and verification status.
  • Saves the collected data to the Apify dataset.

Usage

  1. Run this actor in the Apify console.
  2. Provide the desired input:
    • productUrl: The Sears product URL you want to collect reviews from.

Example Input

1{
2"productUrl": "https://www.sears.com/samsung-ww25b6900aw-a2-2.5-cu-ft-compact-front-load/p-A119240811"
3}

Output

The collected data is saved to the Apify dataset. The output data includes the following fields:

  • review_id: Unique identifier for the review
  • headline: Review title
  • comments: Full text of the review
  • rating: Product rating given by the reviewer
  • nickname: Reviewer's nickname
  • location: Reviewer's location
  • created_date: Date when the review was created
  • updated_date: Date when the review was last updated
  • is_verified_buyer: Whether the reviewer is a verified buyer
  • helpful_votes: Number of helpful votes for the review
  • not_helpful_votes: Number of not helpful votes for the review
  • helpful_score: Overall helpfulness score of the review
  • brand_name: Name of the product brand
  • brand_url: URL of the brand's page
  • product_page_id: Identifier for the product page

Example Output

1{
2    "review_id": 516359579,
3    "headline": "See above! It's  not what I expected from Samsung!",
4    "comments": "I bought this compact Samsung  Washer @  26 March 2024 . The  clothes Washer is extremely loud, vibrates, and sounds like a 1970 Diesel engine. I'm disappointed and will ask for a refund or a motor that doesn't rock the home.   \n\n2.5 cu. ft. Compact Front Load Washer in White with AI Smart Dial and Super Speed Wash\nItem #: 320703807 | Model #: WW25B6900AW | ENERGY STAR Most Efficient",
5    "rating": 2,
6    "nickname": "JD Reiviewer",
7    "location": "Bradenton,  Fl",
8    "created_date": "2024-04-04 02:27:31",
9    "updated_date": "2024-09-19 05:13:45",
10    "is_verified_buyer": false,
11    "helpful_votes": 1,
12    "not_helpful_votes": 1,
13    "helpful_score": 2733,
14    "brand_name": "Samsung - BV",
15    "brand_url": "https://www.samsung.com",
16    "product_page_id": "A119240811"
17}

This example output shows the structured data of a single review. The actual output will be a list of similar objects for all reviews of the specified product.

Notes

  • The collected data is stored in Apify’s default data store.
Developer
Maintained by Community
Actor metrics
  • 2 monthly users
  • 2 stars
  • 100.0% runs succeeded
  • Created in Sep 2024
  • Modified 10 days ago