Multi-Source Inventory Scraping & Website Build | iWeb Data Scraping

Multi-Source Inventory Scraping & New Website Integration
A retail-tech client wanted to aggregate product inventory from 50 different e-commerce websites into a single, unified platform. The new site had to display• Product details ,Pricing information ,Customer reviews The challenge involved two key hurdles: first, consistently scraping data from 50 diverse websites with varying formats and anti-bot defenses; second, building a new website from scratch to unify and display this data in a user-friendly, searchable interface.iWeb Data Scraping delivered a full-stack solution—from multi-site scraping pipelines to a robust front-end interface—that keeps inventory updated automatically.


Goals and Deliverables
Objectives & Deliverables
Core objectives:
- Scrape product details (name, description, specifications, SKU)
- Scrape pricing data (regular, discounted, currency)
- Scrape customer reviews (rating, review text, reviewer name, date)
- Create a central inventory database
- Build a responsive website from scratch to display the aggregated inventory
- Implement search, filters, and sorting for easy navigation
- Schedule automated scraping to keep data fresh
Key deliverables:
- Backend scraping system with modular scrapers for 50 sites
- Centralized product database
- Responsive, SEO-friendly website UI
- Admin dashboard for managing products and scraping schedules
Challenges
- Different site structures: Each website had unique HTML layouts, requiring custom parsers
- JavaScript-heavy content: Many sites required headless browser rendering for data extraction
- Anti-bot measures: Rate limits, captchas, and IP blocking
- Data consistency: Product names, categories, and attributes varied widely across sites
- Review normalization: Different rating scales and formats
- Freshness: Inventory and pricing change frequently; needed scheduled updates


Approach
Step 1: Site Mapping & Requirements Gathering
We audited all 50 target sites to determine:
- Content structure (HTML, JSON APIs, AJAX calls)
- Pagination and product loading methods
- Review availability and formatting
- Anti-bot protections
Step 2: Modular Scraper Development
- Built 50 separate scraper modules using Python, Playwright, and BeautifulSoup
- Extracted product details, prices, and reviews
- Normalized review ratings to a standard 5-star scale
- Stored images with URLs or downloaded as assets
Step 3: Data Normalization
- Standardized product fields (title, description, price, SKU)
- Converted currencies where needed
- Unified category taxonomy for consistent navigation on the new site
Step 4: Inventory Database
- Designed a PostgreSQL database to store scraped data
- Created relations for products, reviews, categories, and sources
- Enabled incremental updates to avoid full re-scrapes
Step 5: New Website Development
- Frontend: React + TailwindCSS for a clean, responsive design
- Backend: Django REST API to serve product data to the frontend
- Features: Search bar, category filters, sort by price/rating/date, product detail pages with reviews
Step 6: Automation & Scheduling
- Integrated Celery task queues for scheduled scraping jobs
- Set update frequency based on each site’s refresh rate (e.g., daily for fast-moving items)
Technical Stack
- Scraping: Python, Playwright, BeautifulSoup4, Requests, Pandas
- Backend: Django REST Framework, PostgreSQL
- Frontend: React, TailwindCSS
- Task Scheduling: Celery + Redis
- Hosting: AWS EC2 + S3 for image storage
- Security: IP rotation, captcha-solving services (where legally permitted), rate limiting to avoid blocking

Sample Data (Illustrative)
Products CSV
Product Name | SKU | Category | Price | Discount Price | Currency | Rating | Review Count | Source Website | Last Updated |
---|---|---|---|---|---|---|---|---|---|
UltraSoft Cotton Tee | UCT-12345 | Clothing > Men | 19.99 | 14.99 | USD | 4.5 | 213 | example-shop.com | 2025-08-14 |
ProGaming Mouse X200 | PGX-200 | Electronics | 49.99 | — | USD | 4.7 | 589 | techgear.com | 2025-08-14 |
Reviews CSV
Product SKU | Reviewer Name | Rating | Review Text | Review Date | Source Website |
---|---|---|---|---|---|
UCT-12345 | John D. | 5 | "Super soft and comfortable." | 2025-08-10 | example-shop.com |
PGX-200 | Sarah P. | 4 | "Great precision, but a bit heavy." | 2025-08-08 | techgear.com |

Results
- Total products collected: 180,000+ across 50 websites
- Reviews aggregated: 1.2M+ customer reviews
- Website launch time: 8 weeks from project start
- Automated updates: Daily for high-change sites, weekly for stable inventories
- Search performance: <300ms response time for queries
Client Impact
- Centralized inventory view: From 50 sources in one place
- Better customer experience: Through search, filtering, and review access
- Time savings: No manual copying of product data from source sites
- Competitive advantage: Real-time pricing and stock updates enable quick market response


Compliance
- Scraped only publicly available data
- Complied with each site’s legal terms and applicable laws
- Rate-limited scraping to avoid service disruption
- Provided opt-out mechanism if a source requested removal
Conclusion
Through a combination of advanced web scraping, robust data normalization, and full-stack development, iWeb Data Scraping successfully delivered a unified platform that aggregates inventory, pricing, and reviews from 50 different e-commerce websites. The solution not only automated data collection but also provided a seamless, user-friendly website with powerful search and filtering features. By integrating Product Availability Services and Price Tracking Services , alongside specialized solutions like Grocery & Supermarket Data Extraction Services and Quick Commerce & FMCG Data Extraction Services , the project ensured real-time updates, scalability, and compliance with legal standards. This empowered the client with a centralized, competitive, and future-ready platform. The case demonstrates how tailored scraping pipelines combined with modern web technologies can transform fragmented data into actionable business value.
📩 Email Us:
✉️ info@iwebdatascraping.com
📞 Call or WhatsApp:
📱 +1 (424) 377-7584
Source>> https://www.iwebdatascraping.com/multi-source-inventory-scraping-new-website-integration.php
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