Thunderbit scrapes web data from a plain description rather than a selector. Pre-built templates cover Amazon, eBay and Google Maps, and the output exports directly to Excel, Google Sheets, Airtable or Notion, with summarisation, categorisation and translation applied on the way through.
Transforming during extraction is what saves the second step. Conventional scrapers return raw text that then needs cleaning, categorising and often translating before anyone can use it, and that post-processing is usually longer than the scrape. Article and transcript scraping extends it past structured listings.
Thunderbit reports 200,000 users, 4.8 on Capterra and a Chrome extension, free to start with paid tiers not detailed on the page. Web scraping carries terms-of-service and data protection questions the user owns, not the tool; scrapers break when sites change layout regardless of how they are configured; and AI-categorised output still needs checking before it drives outreach.
