AI_SCRAPE
Scrape a URL and extract structured data using AI and natural language
=AI_SCRAPE(url, description, [renderJs])Devuelve: string[][]
Descripción General
AI_SCRAPE combines web scraping and AI extraction into a single powerful formula. Give it a URL and describe in plain English what data you want, and it fetches the page, reads its content, and returns a clean structured table with exactly the information you asked for. No CSS selectors, no XPath expressions, no inspecting HTML elements — just tell the AI what you need in natural language and it figures out how to extract it from whatever page structure it encounters.
Parámetros
| Parámetro | Tipo | Requerido | Descripción |
|---|---|---|---|
url | string | Sí | The full URL of the web page to scrape, including the protocol (https://). |
description | string | Sí | A natural language description of what data to extract from the page. Be specific about the fields you want. |
renderJs | boolean | No | Set to TRUE to render JavaScript before extracting data. Required for SPAs and dynamic pages. Slower but necessary for JS-heavy sites. |
Ejemplos
Extract product info from an e-commerce page
Scrapes a product page and extracts key product details into a structured table.
=AI_SCRAPE("https://store.example.com/product/wireless-headphones", "product name, price, rating, number of reviews")Salida
| Product Name | Price | Rating | Number of Reviews |
| ProSound Wireless Headphones | $149.99 | 4.5/5 | 2,347 |
Scrape job listings from a careers page
Extracts all job openings from a company careers page into a structured list.
=AI_SCRAPE("https://company.example.com/careers", "job title, department, location, employment type")Salida
| Job Title | Department | Location | Employment Type |
| Senior Frontend Engineer | Engineering | Remote | Full-time |
| Product Designer | Design | New York, NY | Full-time |
| Data Analyst | Analytics | San Francisco, CA | Full-time |
| Content Marketing Manager | Marketing | Remote | Full-time |
Monitor competitor pricing with JS rendering
Scrapes a JavaScript-rendered pricing page to monitor competitor plans and pricing changes.
=AI_SCRAPE("https://competitor.example.com/pricing", "plan name, monthly price, annual price, key features", TRUE)Salida
| Plan Name | Monthly Price | Annual Price | Key Features |
| Starter | $9/mo | $7/mo | 5 users, 10GB storage |
| Professional | $29/mo | $24/mo | 25 users, 100GB, API access |
| Enterprise | Custom | Custom | Unlimited users, SSO, SLA |
Extract news headlines and dates
Pulls the latest news articles from a tech news page into a tracking spreadsheet.
=AI_SCRAPE("https://news.example.com/tech", "headline, date published, author, summary")Salida
| Headline | Date Published | Author | Summary |
| AI Startup Raises $50M Series B | Jan 15, 2025 | Jane Smith | The startup plans to expand its enterprise offering... |
| New Framework Challenges React | Jan 14, 2025 | John Doe | A new JavaScript framework promises faster performance... |
Bulk scrape from a URL list
References a URL in cell A2. Drag down a column of company website URLs to build a research database.
=AI_SCRAPE(A2, "company name, description, founding year, headquarters")Salida
| Company Name | Description | Founding Year | Headquarters |
| TechCorp | Enterprise cloud infrastructure provider | 2015 | Austin, TX |
Casos de Uso
Competitive Pricing Intelligence
Monitor competitor product prices daily by scraping their product pages. Build a pricing database in Sheets that updates with fresh data, helping you adjust your own pricing strategy in real time.
Lead Generation and Prospecting
Scrape company directories, industry lists, and LinkedIn company pages to extract contact information, company size, and industry data for building targeted outreach lists.
Real Estate Market Monitoring
Track property listings across multiple real estate websites, extracting price, square footage, bedrooms, and location data to build a comprehensive market analysis spreadsheet.
Academic Research Data Collection
Scrape data from government databases, research repositories, and public datasets that do not offer API access, converting web-based tables and reports into analyzable spreadsheet data.
Brand Mention Monitoring
Monitor news sites, review platforms, and industry blogs for mentions of your brand, extracting the headline, date, sentiment, and source URL into a media tracking sheet.
Job Market Intelligence
Track competitor job postings to understand their hiring priorities, salary ranges, and team growth areas, providing strategic intelligence for your own talent planning.
Consejos Profesionales
Be as specific as possible in your description. Instead of "get all the data", say "product name, price in USD, star rating out of 5, number of customer reviews". Specific descriptions produce dramatically cleaner output.
For monitoring use cases, set up your scraping sheet once with URLs in column A and AI_SCRAPE formulas in column B. Refresh the sheet periodically to get updated data without rebuilding anything.
Chain AI_SCRAPE with AI_CLASSIFY or AI_EXTRACT for a two-pass workflow: first scrape raw page content, then classify or further structure the results in a second step for more precise extraction.
Only enable renderJs when needed. Static scraping is significantly faster and cheaper. Test without it first, and only enable JavaScript rendering if the results are empty or incomplete.
This approach solves the biggest pain point of traditional web scraping: fragile selectors that break whenever a website updates its layout. Because AI_SCRAPE uses semantic understanding rather than hardcoded element paths, it adapts to different page structures automatically. A single formula can extract product prices from Amazon, Shopify, WooCommerce, and custom e-commerce sites without any changes to the extraction logic. The AI understands what a "price" is regardless of whether it is in a span with class "price-tag", a div with data-testid="product-price", or plain text inside a paragraph.
The optional renderJs parameter enables JavaScript rendering for modern single-page applications (SPAs) that load content dynamically. When set to true, the function launches a headless browser to fully render the page before extraction, making it possible to scrape data from React, Vue, Angular, and other JavaScript-heavy sites. For static HTML pages, leave this parameter off to get faster results. AI_SCRAPE is ideal for competitive monitoring, lead generation, research data collection, and any workflow where you need web data in your spreadsheet without building and maintaining a dedicated scraping infrastructure.
Errores Comunes
#ERROR! Failed to fetch URLCausa: The URL is inaccessible, the server returned an error, or the domain does not exist.
Solución: Verify the URL is correct and accessible in your browser. Check for typos in the domain name. Ensure the URL starts with "https://" or "http://". Some sites may block automated access — try enabling renderJs.
#ERROR! No data found matching descriptionCausa: The AI could not find content matching your description on the page.
Solución: Refine your description to better match what is actually on the page. Visit the page in your browser to verify the data exists. If the page loads content via JavaScript, enable renderJs=TRUE.
#ERROR! Page requires JavaScriptCausa: The page uses JavaScript to load content dynamically, and static scraping returned an empty or incomplete page.
Solución: Add TRUE as the third parameter to enable JavaScript rendering: =AI_SCRAPE(url, description, TRUE). This launches a headless browser to fully render the page before extraction.
#ERROR! Request timeoutCausa: The page took too long to load, exceeding the function timeout limit.
Solución: The target server may be slow or overloaded. Try again in a few minutes. For JavaScript-rendered pages, timeouts are more common due to additional rendering time.
Preguntas Frecuentes
Enable JavaScript rendering when the page loads content dynamically using frameworks like React, Vue, or Angular, or when the data you need appears only after the page fully loads. Signs that you need JS rendering: the page shows a loading spinner, content appears after a delay, or static scraping returns empty results. Note that JS rendering is slower and uses more resources.
No, AI_SCRAPE can only access publicly available web pages. Pages behind login walls, paywalls, or authentication will return an error or the login page content. For authenticated scraping, you would need a dedicated scraping solution.
SCRAPE_BY_CSS_PATH requires you to specify exact CSS selectors (like "div.price > span") and returns raw HTML content. AI_SCRAPE uses natural language descriptions and returns clean, structured data. Use AI_SCRAPE when you want ease of use and adaptability; use SCRAPE_BY_CSS_PATH when you need precise control over exactly which HTML element to extract.
Web scraping legality depends on the website's terms of service, the jurisdiction, and how you use the data. Generally, scraping publicly available data for personal research or competitive analysis is accepted practice. Always check the website's robots.txt file and terms of service. Do not scrape personal data, copyrighted content for republication, or data behind access controls.
Some websites block automated requests via CAPTCHAs, rate limiting, or IP blocking. If a scrape fails, the function returns an error. Try again after a few minutes. For consistently blocked sites, consider using renderJs=TRUE or reducing the frequency of requests.
AI_SCRAPE processes one URL per call. To scrape paginated results, put each page URL in a separate row (e.g., page1, page2, page3) and run AI_SCRAPE on each. You can construct pagination URLs using formulas like ="https://example.com/results?page=" & ROW(A1).
Funciones Relacionadas
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