Home Appliance Data to Excel
Budget: ₹600 – ₹1,500 INR
I need the product information for current-model home appliances gathered from leading comparison websites and delivered in a clean, well-structured Excel workbook.
Scope
• Target category: home appliances only, no other product lines.
• Source: public comparison websites (not manufacturer or single-store pages).
• Fields required: product name, full description, customer reviews and numerical ratings. Prices and stock status are not needed this time.
Dataset expectations
A single .xlsx file separated by appliance type (e.g., refrigerators, washing machines, microwaves) on individual sheets. Each sheet should list:
– Product Name
– Description (paragraph form, no HTML tags)
– Average Rating (numeric)
– Review Text (one row per review, repeat product name if necessary)
Include a brief README sheet that explains any column codes or scraping limitations you encountered.
Technical notes
Feel free to use Python, Scrapy, BeautifulSoup, Selenium or a similar scraper—whatever you are fastest with—provided the final data is accurate, deduplicated and ready for pivot-table analysis. If you plan on using an API or paid proxy service, let me know in advance so I can approve the approach.
Acceptance criteria
1. At least 300 unique home-appliance models covered.
2. Data accuracy spot-checked at 95 % or higher against live pages.
3. No blocked URLs or CAPTCHA text left in the cells.
Once the workbook passes the checks, the project is complete. Let me know your estimated turnaround and any questions you have about specific comparison sites.
Scope
• Target category: home appliances only, no other product lines.
• Source: public comparison websites (not manufacturer or single-store pages).
• Fields required: product name, full description, customer reviews and numerical ratings. Prices and stock status are not needed this time.
Dataset expectations
A single .xlsx file separated by appliance type (e.g., refrigerators, washing machines, microwaves) on individual sheets. Each sheet should list:
– Product Name
– Description (paragraph form, no HTML tags)
– Average Rating (numeric)
– Review Text (one row per review, repeat product name if necessary)
Include a brief README sheet that explains any column codes or scraping limitations you encountered.
Technical notes
Feel free to use Python, Scrapy, BeautifulSoup, Selenium or a similar scraper—whatever you are fastest with—provided the final data is accurate, deduplicated and ready for pivot-table analysis. If you plan on using an API or paid proxy service, let me know in advance so I can approve the approach.
Acceptance criteria
1. At least 300 unique home-appliance models covered.
2. Data accuracy spot-checked at 95 % or higher against live pages.
3. No blocked URLs or CAPTCHA text left in the cells.
Once the workbook passes the checks, the project is complete. Let me know your estimated turnaround and any questions you have about specific comparison sites.