Fashionable Pincodes: Amazon Bestseller Scraper

Project Overview:

We need a web scraper that extracts best-selling fashion products (women’s tops, shirts, crop tops, bottom wear, and men’s shirts, T-shirts, and bottom wear) from Amazon and organizes the data based on pincode-wise popularity. The scraper should be automated to collect data daily and store it in Google Sheets or a database.

Key Requirements:
1. Scrape Bestseller Data
• Extract product details such as name, price, discount, ratings, brand, category, and product URL from Amazon’s bestseller section.
2. Pincode-Based Scraping
• The scraper should fetch bestseller data for different locations (pincode-wise) to analyze regional trends.
• Implement a method to collect data for multiple pincodes in major cities like Pune, Mumbai, Bangalore, and Delhi.
3. Automation & Scheduling
• The scraper should run automatically on a daily basis and store historical data.
• Allow flexibility to add more locations or categories in the future.
4. Amazon Anti-Bot Handling
• Implement techniques like rotating proxies, user agents, CAPTCHA solving, and other necessary anti-bot bypassing methods to ensure smooth scraping.
5. Data Storage & Export
• Store extracted data in Google Sheets or a structured database for easy access.
• Ensure smooth integration for data analysis and visualization.

Deliverables:
• Working Python Scrapy/Selenium scraper
• Automated daily data collection
• Data output in Google Sheets or database
• Documentation on how to use and modify the scraper

Question:
• How much would you charge for developing this Amazon bestseller scraper with pincode-based data collection?
• Would you require additional services like proxies or CAPTCHA solving to ensure Amazon does not block the scraper?
Next Steps:

To evaluate feasibility, please provide a sample dataset of 2 bestseller pages for 10–15 different pincodes in Pune or Mumbai.