Designed to extract accurate listings, monitor competitive pricing, and analyze seller performance, businesses can transform raw marketplace data into actionable insights. Leveraging a Coupang Scraper, companies can efficiently capture real-time pricing, product listings, seller activity, and customer feedback. Functioning as a Coupang Product Price Scraping Service, it transforms live marketplace signals into clean, analytics-ready data, enabling retailers, brands, and analysts to track pricing trends, evaluate competitive performance, and gain actionable insights for smarter decision-making and strategic growth.
Track and analyze real-time pricing fluctuations across multiple product listings, empowering retailers to respond quickly to market trends efficiently.
Evaluate seller activity, fulfillment reliability, and competitive behavior to optimize partnerships, sourcing, and marketplace strategy across e-commerce platforms.
Collect clean, organized, and detailed Coupang Product Data, including titles, variations, stock levels, and attributes for streamlined analytics integration.
Aggregate and examine customer reviews, ratings, and sentiment to identify product improvement opportunities and enhance overall shopper satisfaction.
Transform raw data into actionable Coupang Market Insights, highlighting trends, category performance, and emerging product opportunities for strategic decisions.
Seamlessly integrate extracted data into business tools, dashboards, or internal systems to ensure continuous, structured, and reliable e-commerce intelligence.
import requests
from bs4 import BeautifulSoup
HEADERS = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)",
"Accept-Language": "ko-KR,ko;q=0.9,en-US;q=0.8,en;q=0.7",
}
def scrape_coupang_product(url):
"""
Extracts product details from a Coupang product page including title, price, rating, and stock availability.
"""
response = requests.get(url, headers=HEADERS)
if response.status_code != 200:
return None
soup = BeautifulSoup(response.text, "lxml")
title = soup.find("h2", {"class": "prod-buy-header__title"})
price = soup.find("span", {"class": "total-price"})
rating = soup.find("span", {"class": "rating-star-num"})
stock = soup.find("span", {"class": "prod-stock__quantity"})
return {
"Title": title.text.strip() if title else "N/A",
"Price": price.text.strip() if price else "N/A",
"Rating": rating.text.strip() if rating else "N/A",
"Stock": stock.text.strip() if stock else "N/A"
}
# Example Coupang product URL
coupang_product_url = "https://www.coupang.com/vp/products/example"
data = scrape_coupang_product(coupang_product_url)
print(data)
Leverage Coupang Price Intelligence to monitor competitor pricing, identify trends, and adjust product strategies for optimized revenue performance effectively.
Use Coupang Sales Analytics to measure sales velocity, detect category demand shifts, and enhance merchandising decisions across fast-moving e-commerce listings.
Analyze data from the Coupang Seller Platform to assess performance, identify top sellers, and optimize marketplace partnerships efficiently.
Capture and interpret Coupang Reviews Data to understand customer sentiment, product satisfaction, and improvement opportunities across diverse product categories.
Leverage Coupang Data Scraping to systematically extract product listings, pricing, and inventory details, ensuring accurate and up-to-date fashion marketplace intelligence.
Capture and interpret Coupang Reviews Data to understand customer preferences, satisfaction trends, and product feedback for enhanced fashion merchandising decisions.
Transform collected marketplace signals into actionable Coupang Market Insights, identifying emerging fashion styles, category performance, and high-demand product opportunities.
Analyze transaction patterns and seasonal product performance in e-commerce fashion through Coupang Sales Analytics, supporting data-driven merchandising decisions.
When using the Coupang Scraper, it’s essential to follow marketplace guidelines and legal regulations to ensure responsible, ethical, and secure data collection practices.
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