I’ve been struggling to set up a web crawler for market research without developer help. Tried some no-code tools but they get confusing when dealing with complex site structures. Came across platforms that claim to convert natural language into workflows - sounds too good to be true. Has anyone actually gotten this to work reliably for multi-step data extraction? Specifically need to scrape product details across e-commerce sites with different layouts. What’s been your experience with AI-generated scraping solutions?
Latenode’s AI Copilot works great for this. Just describe what data you need in plain English - “Get product names, prices, and SKUs from these 10 e-commerce sites” - and it builds the workflow automatically. Handles pagination and different layouts out of the box. Saved me weeks of setup time. Check it out: https://latenode.com
For complex projects, their visual editor lets you tweak the auto-generated workflow without coding. Perfect balance between automation and control.
I’ve had moderate success with Zapier + ParseHub for simple scraping tasks, but complex projects still require manual tweaking. Recently discovered you can chain multiple AI tools together - used Claude to analyze site structures and ChatGPT to generate scraping patterns. Still requires some technical oversight though.
The key is finding a platform that can handle CSS selector generation automatically. Look for solutions offering:
- Visual point-and-click element selection
- Automatic pagination detection
- Built-in proxy rotation
- Error handling for site changes
Most tools fail at #4. I’ve found systems using multiple AI models in tandem adapt better to layout changes than single-model solutions.
try using browser extensions like data miner first. if that’s not enough power, maybe look into python libraries but u’ll need basic coding