A mid-sized market research firm needed to aggregate pricing, product details, and customer reviews from multiple e-commerce sites—both static and heavily JavaScript-driven—to fuel their quarterly competitor analysis reports.

𝐓𝐢𝐦𝐞-𝐜𝐨𝐧𝐬𝐮𝐦𝐢𝐧𝐠 𝐦𝐚𝐧𝐮𝐚𝐥 𝐜𝐨𝐥𝐥𝐞𝐜𝐭𝐢𝐨𝐧: Analysts were spending 20+ hours per Week copying and pasting data. 𝐂𝐨𝐦𝐩𝐥𝐞𝐱 𝐬𝐢𝐭𝐞 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞𝐬: Some target sites used dynamic loading, lazy-loading elements, and login walls. 𝐃𝐚𝐭𝐚 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐢𝐬𝐬𝐮𝐞𝐬: Inconsistent structures led to missing fields and duplicate entries.

✦ Fully automate data extraction from up to three target sites.

✦ Deliver clean, deduplicated, and structured output in their BI tool–ready formats (CSV and JSON).

✦ Provide clear instructions so the in-house team could run or modify the scraper after handover.

𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 & 𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠: Reviewed target site architectures (static HTML vs. JS-heavy). Defined the exact data points (e.g., product name, price, review text, star rating). 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Built with Scrapy for static pages, Selenium + BeautifulSoup for dynamic content and login flows.Implemented proxy rotation and randomized delays to avoid IP bans. 𝐃𝐚𝐭𝐚 𝐂𝐥𝐞𝐚𝐧𝐢𝐧𝐠 & 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧: Normalized date formats, stripped HTML tags, and removed duplicates.Added schema validation to ensure all required fields were present. 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 & 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠: Packaged the scraper as a self-contained Python script.Provided a one-page “Runbook” with setup steps, dependency installation, and troubleshooting tips.

𝐓𝐢𝐦𝐞 𝐬𝐚𝐯𝐞𝐝: Automated monthly data collection reduced manual effort by 95% (from 20+ hours to under 1 hour of scheduled runs).

𝐃𝐚𝐭𝐚 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲: 0% missing fields on critical attributes; duplicates eliminated.

𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐯𝐚𝐥𝐮𝐞: Enabled analysts to spend more time on insights rather than data gathering—directly contributing to faster report turnaround and more timely market recommendations.

𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬 & 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬: Python, Scrapy, Selenium, BeautifulSoup

𝐃𝐚𝐭𝐚 𝐅𝐨𝐫𝐦𝐚𝐭𝐬: CSV, Excel, JSON, Google Sheets

API 𝐀𝐮𝐱𝐢𝐥𝐢𝐚𝐫𝐲: Requests, Pandas, Schema (for validation), Cron (for scheduling)

“Mudasir delivered great work for this project and I enjoyed working with him. His communication was top-notch, he met all deadlines, and his skills were strong! Highly recommended.”