How to Scrape Sam's Club Product, Search, and Review Details

Sam’s Club is a major membership-only warehouse club offering a wide range of products, from groceries to electronics. Since its founding in 1983, Sam’s Club has expanded to include:

• Nearly 600 stores across the U.S. and Puerto Rico
• Thousands of products across categories like home goods, appliances, and groceries

With millions of members shopping both in-store and online, Sam’s Club data offers valuable insights for brands, analysts, and market researchers. Companies can track real-time pricing fluctuations, monitor product availability, and analyze customer feedback through reviews and ratings

However, scraping data from Sam’s Club comes with challenges like CAPTCHA protection, rate limiting, and IP blocking. This makes data extraction difficult without a robust scraping solution.

Why Use Unwrangle?

Manually scraping Sam’s Club data can be time-consuming and technically challenging due to anti-scraping protections. Unwrangle eliminates these complexities, offering a seamless way to access Tesco products and review data.

With Unwrangle, you get:

• Hassle-Free Scraping: No need to deal with CAPTCHAs, rate limits, or IP bans.

• Reliable & Up-to-date Data: Get accurate pricing, descriptions, and customer reviews without interruptions.

• Structured JSON Responses: Easily integrate the data into your applications without messy parsing.

• Time & Cost Efficiency: Save development time and resources by using a ready-made solution.

In this tutorial, we’ll walk you through scraping Sam’s Club using Unwrangle API with Python.

What We Will Scrape Today

• Sam’s Club Product Data: Product descriptions, specifications, pricing, availability, images, and more.

• Sam’s Club Product Reviews: Customer reviews, including ratings, review titles, review text, and submission dates.

• Sam’s Club Search Results: Extracting product listings returned for specific search queries, including product IDs, names, categories, and prices.

Let’s get started!

Scraping Sam's Club with Unwrangle API Using Python

Step 1: Prerequisites

Before you begin, ensure you have the following:

• API Key: Sign up on Unwrangle to get your API key.

• Python Installed: Ensure Python 3.x is installed on your system.

• Requests Library: Install the requests library if you don’t already have it by running:
  pip install requests

Step 2: Making a Basic API Request

To scrape Sam’s Club data, you need to make a GET request to the /api/getter endpoint with the following query parameters:

• Platform: Specifies the API type (samsclub_detail, samsclub_reviews, or samsclub_search).

• URL/Search: Provide the product URL, search term, or other details based on the API type.

• API Key: Authenticate the request with your Unwrangle API key.

• Additional Parameters: Optional parameters such as page number.

Sam’s Club API Query Parameters

Parameter	Description	Required/Optional	Default Value
platform	Specifies the scraping engine (e.g., samsclub_detail, samsclub_reviews, samsclub_search).	Required	None
api_key	Your API token.	Required	None
url	Product listing URL on SamsClub.com.	Required	None
search	The keyword used in a search query (e.g., laptop).	Required (for search)	None
page	Page number for pagination.	Optional	1

Sam’s Club Product Data API

Scrape detailed Sam’s Club product information with a single API call.

Example: Scraping Product Details

Results:

Sam’s Club Product Reviews API

Scrape Sam’s Club customer reviews in real-time with a simple API call.

Example: Scraping Product Reviews

Results:

Sam’s Club Search Results API

Scrape Sam’s Club search results directly from their search engine.

Example: Scraping Search Results

Results:

Need a Complete E-commerce Data Solution? Try Unwrangle

Unwrangle's E-commerce APIs provide a simple solution:

• Fetch real-time product details, search results, and customer reviews

• Skip the hassle of configuring parsers, rotating proxies, or solving CAPTCHAs

• Get structured JSON responses with a simple HTTP request

Sign up today and start scraping data from major e-commerce retailers.