n8n Web Scraping Workflow Builder
Budget: ₹600 – ₹1,500 INR
I need a rock-solid n8n workflow that, whenever I trigger it, navigates through selected e-commerce sites and public business directories, captures every piece of business information that is publicly available, and stores it in a clean, query-ready format. The data I care about includes the business name, category or type, “about” text, founders’ names, any additional corporate details the site reveals, plus all images properly downloaded and tagged. I will be running various data-analysis models on the output, so accuracy, consistency, and tidy structuring are non-negotiable.
The flow must:
• Accept a list of target URLs and run on demand (no fixed schedule).
• Respect robots.txt and site rate limits while still remaining efficient.
• Handle pagination, lazy-loaded sections, and common anti-bot measures.
• Output to a well-structured destination of your choice—PostgreSQL, Airtable, or a neatly formatted CSV/JSON in an S3 bucket all work for me—as long as the schema is documented and repeatable.
• Deliver meaningful logging and alerts so I immediately know if a job fails or a selector breaks.
Please build the solution entirely inside n8n, using built-in nodes or custom JavaScript/TypeScript functions where necessary, and keep it modular enough that I can add new sites later without rewriting the whole flow. I’ll consider the job complete once you provide:
1. The exportable n8n workflow file.
2. A short README explaining how to supply new URLs, start a run, and locate the results.
3. A quick screenshare or video walkthrough demonstrating one successful scrape end-to-end.
If you’ve tackled similar large-scale extractions before, I’d love to see an example.
The flow must:
• Accept a list of target URLs and run on demand (no fixed schedule).
• Respect robots.txt and site rate limits while still remaining efficient.
• Handle pagination, lazy-loaded sections, and common anti-bot measures.
• Output to a well-structured destination of your choice—PostgreSQL, Airtable, or a neatly formatted CSV/JSON in an S3 bucket all work for me—as long as the schema is documented and repeatable.
• Deliver meaningful logging and alerts so I immediately know if a job fails or a selector breaks.
Please build the solution entirely inside n8n, using built-in nodes or custom JavaScript/TypeScript functions where necessary, and keep it modular enough that I can add new sites later without rewriting the whole flow. I’ll consider the job complete once you provide:
1. The exportable n8n workflow file.
2. A short README explaining how to supply new URLs, start a run, and locate the results.
3. A quick screenshare or video walkthrough demonstrating one successful scrape end-to-end.
If you’ve tackled similar large-scale extractions before, I’d love to see an example.
Related categories:
Python
Excel
Web Scraping
Data Mining
PostgreSQL
Data Analysis
API Integration
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