Prompt
Need low-code crawling for lots of websites
Latest observation
If you need low-code crawling for lots of websites, the best fit is usually a tool that gives you:
- visual extraction / point-and-click selectors
- scheduling
- pagination / infinite scroll support
- batch runs across many URLs
- export to CSV/JSON/Google Sheets/webhooks
- ideally anti-bot handling and browser automation
Good low-code options
-
Browse AI
- Very low-code
- Good for monitoring pages and extracting structured data
- Easy to train on one page and run on many similar pages
-
Octoparse
- Strong for bulk scraping
- Visual workflow builder
- Handles pagination, scrolling, and some dynamic sites
-
Apify
- More powerful, still fairly low-code
- Great for scaling across many sites
- Has ready-made actors and scheduling
- Better if you need more than simple extraction
-
Phantombuster
- Good for workflows around social/media/public web data
- Less ideal for arbitrary complex websites, but very easy to use
-
WebHarvy
- Desktop-based visual scraper
- Good for straightforward sites
- Less suitable for large-scale cloud crawling
Best choice by use case
- Fastest/easiest: Browse AI
- Best general bulk crawling: Octoparse
- Best for scaling and automation: Apify
- Best for simple desktop use: WebHarvy
What to watch out for
- Many websites block aggressive crawling
- Different layouts across sites reduce automation reliability
- Login-required sites may need browser-based tools
- Check terms of service and robots policy before scraping
A practical setup for “lots of websites”
If you mean hundreds or thousands of similar sites/pages, I’d usually recommend:
- Apify if you want scale and reliability
- Octoparse if you want a GUI and don’t want to code
- Browse AI if you mostly need monitoring/extraction from a manageable number of sites
If you want, I can give you a shortlist based on your exact needs:
- websites are static or dynamic
- do you need login
- how many sites/pages
- what data you want
- where you want the output to go (CSV, Sheets, API, database)
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
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