Customer reviews are among the strongest forms of digital feedback; they reveal satisfaction, frustration, expectations, and purchase behavior. Diya Infotech’s Reviews Data Scraping Services help businesses extract customer reviews from eCommerce platforms, apps, social media sites, and third-party websites at scale to generate insights, track sentiment, and inform decision-making.
Reviews Data Scraping Solution for Actionable Customer Insights
With Reviews Data Scraping, you can:
- Collect product & service reviews from multiple platforms
- Extract ratings, feedback text, reviewer details, timestamps & more
- Analyze sentiment trends & satisfaction levels
- Identify product improvement & innovation opportunities
- Track competitor reviews side-by-side for benchmarking
What is Reviews Data Scraping?
Reviews Data Scraping is the process of automating the extraction of customer reviews from online platforms like Amazon, Flipkart, Google, TripAdvisor, Zomato, Yelp, app stores, community forums, and social media. Instead of manually reading thousands of reviews, scraping collects them in bulk and converts them into structured data for analysis.
This data includes star ratings, written reviews, reviewer profiles, location, sentiment, product quality remarks, complaints, and feature feedback. By analyzing them, businesses understand real customer pain points, demand expectations, product satisfaction levels, and areas requiring improvement.
Reviews scraping is used by eCommerce brands, D2C companies, SaaS platforms, restaurants, travel brands, and manufacturers to improve product experience, compare competitors, and make better business decisions. It transforms raw customer feedback into valuable intelligence, helping brands prioritize features, improve service, and build products customers love.
Benefits of Reviews Data Scraping
Reviews data scraping captures authentic customer opinions, helping businesses identify issues, improve products, and make informed decisions faster.
Use Cases of Reviews Data Scraping
Product Feedback Insights
Analyze customer reviews to refine quality, features & packaging.
Brand Sentiment Tracking
Monitor the emotional tone of reviews over time to track perception.
Competitor Review Comparison
Study competitor reviews to spot weaknesses & gain an advantage.
Feature & Complaint Patterning
Identify the most mentioned features, issues & expectations.
CX & Quality Reporting
Build insights dashboards for internal teams to act quickly.
Fake Review Detection
Identify suspicious or low-quality reviews to improve data reliability and decision-making.
How Diya Infotech’s Reviews Data Scraping Works
Data Source Identification
Platforms are shortlisted (Amazon, Google, App Store, OTA, marketplace, etc.) based on requirements.
01
Automated Review Extraction
Reviews are scraped at scale with star ratings, timestamps, sentiments & metadata.
02
Cleaning & Structuring
Data is normalized to remove duplicates, tagging sentiment & features for clarity.
03
Insight Analysis & Segmentation
Reviews are categorized into topics (taste, delivery, quality, pricing, etc.) for deeper insights.
04
Delivery & Integration
Outputs are delivered via Excel/CSV, APIs, or dashboards ready for analytics or reporting.
05
What Sets Us Apart
Accuracy
Delivers clean, reliable data you can trust every time.
Scalability
Handles any data volume smoothly without slowdown.
Global Reach
Captures insights from markets across the world.
Real-Time APIs
Provides instant, up-to-date data on demand.
Compliance First
Ensures all data practices meet global standards.
Dedicated Support
Project-based dedicated support 24*7.
Other Industries
Get In Touch
We are your preferred data services partner. Our commitment to your success begins when you fill up this form and send it to us.
What's Next ?
You have made the right choice by connecting with us for your data extraction requirements. The below process how to get started.