Universal Review Scraping Service

Datazivot's Universal Review Scraping Service enables businesses to extract and analyze customer reviews from multiple platforms across key global markets, including Japan, Canada, Italy, Germany, USA, UK, UAE, Australia, China, Switzerland, Qatar, India, Singapore, Macao SAR, Ireland, Austria, Denmark, Luxembourg, and Norway. Our advanced tools provide universal reviews collection, universal customer feedback data analysis, and universal reviews data analysis services to help brands make data-driven decisions. Effortlessly extract universal reviews for enhanced customer insights.

Universal-Review-Scraping-Service

How Does Universal Review Scraping Service Work?

Our Universal Review Scraping Service works by using universal reviews data harvesting services to extract, collect, and analyze customer feedback from various platforms, delivering actionable insights for businesses.
Input-Configuration

Data Collection

Datazivot gathers data from various sources using advanced web scraping techniques and APIs to ensure comprehensive coverage.
Web-Scraping-Execution

Data Cleaning & Analysis

The collected data is cleaned, structured, and analyzed to extract meaningful insights, making it ready for use.
Data-Retrieval-Output

Delivery & Integration

The processed data is delivered in user-friendly formats and can be integrated into client systems for real-time access to insights.

Universal Review Scraping API

Our Universal Review Scraping API enables businesses to effortlessly extract, analyze, and harness customer feedback from multiple platforms for informed decision-making.
                                                            
import requests
from bs4 import BeautifulSoup
# URL of the page you want to scrape
url = 'https://play.google.com/store/apps/details?id=com.flipkart.shopsy&hl=en_GB&pli=1'
# Send a GET request to the URL
response = requests.get(url)
# Parse the HTML content of the page with BeautifulSoup
soup = BeautifulSoup(response.text, 'html.parser')
# Find all review divs
reviews = soup.find_all('div', class_= 'review-container')
# Iterate over each review and extract the necessary information
for review in reviews:
# Extract the review title
title = review.find('span', class_='noQuotes').text.strip()
# Extract the review rating
rating = review.find('span', class_='ui_bubble_rating')['class'][1]
# Extract the review text
text = review.find('p', class_='partial_entry').text.strip()
# Print the review details
print(f"Title: {title}/nRating: {rating}/nText: {text}/n---")
                                                            
{
status: 200,
"source_url": "https://play.google.com/store/apps/details?id=com.flipkart.shopsy&hl=en_GB&pli=1",
"review_count": 12.1M,
"average_rating": 4.3,
}

Benefits of Universal Review Scraping

Universal Review Scraping Use Cases

Universal review scraping enables businesses to gather insights on customer feedback, track competitor performance, enhance product development, optimize marketing strategies, and improve overall customer satisfaction.

Market-Research-Insights
Market Insights
Businesses can utilize Universal Reviews Scraping Service to gather customer feedback across platforms, enabling comprehensive universal reviews collection and market insights.
Competitor-Analysis
Competitor Analysis
Extract universal reviews from competitors to identify strengths and weaknesses, helping brands refine their strategies based on universal customer feedback data analysis.
Product-Development-Feedback
Product Enhancement
Analyzing customer reviews through universal reviews data analysis services allows companies to make informed decisions on product features, enhancing user satisfaction.
Brand-Reputation-Management
Sentiment Tracking
Track sentiment trends over time using universal reviews data gathering tools, providing insights into how public perception of products changes.
Sentiment-Analysis
Reputation Management
Leverage universal reviews data harvesting services to monitor and manage brand reputation by addressing negative feedback and reinforcing positive experiences.
Content-Generation
Marketing Optimization
Use collected reviews to tailor marketing messages, ensuring alignment with customer expectations and preferences derived from universal reviews collection.
Price-Monitoring
Sales Evaluation
Analyze reviews to correlate customer feedback with sales performance, identifying factors that drive or hinder success in the market.
Customer-Feedback-Integration
Support Improvement
Gather insights from reviews to improve customer support, addressing common issues and enhancing service quality based on universal customer feedback data analysis.

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