Convert URL HTML to Markdown and Get Page Links

This workflow utilizes advanced AI language models and web data scraping technologies to automate the research and structuring of corporate information. Users can process lists of companies in bulk, accurately obtaining various key information such as company domain names, LinkedIn links, and market types. The results are automatically updated to Google Sheets for easier management and analysis. This system significantly enhances data collection efficiency, addressing issues of incomplete information and outdated updates commonly found in traditional manual research. It is suitable for scenarios such as market research, sales lead generation, and investment due diligence.

This workflow automatically scrapes and analyzes LinkedIn profiles to extract key information and calculate ICP scores, enabling precise evaluation of sales leads and candidates. Users only need to manually initiate the workflow, and the system can automatically access LinkedIn, analyze the data, and update it to Google Sheets, achieving a closed-loop data management process. This significantly improves work efficiency, reduces manual operations, and ensures the timeliness and accuracy of information, making it suitable for various scenarios such as sales, recruitment, and market analysis.

This workflow automates the retrieval of website traffic data from Google Analytics and conducts a two-week comparative analysis using AI, generating SEO reports and optimization suggestions. After intelligent data processing, the results are automatically saved to a Baserow database, facilitating team sharing and long-term tracking. It is suitable for website operators and digital marketing teams, enhancing work efficiency, reducing manual operations, and providing data-driven SEO optimization solutions to boost website traffic and user engagement.

This workflow demonstrates how to flexibly handle date and time data, including operations such as addition and subtraction of time, formatted display, and conversion from ISO strings. Users can quickly calculate and format time through simple node configurations, addressing common date and time processing needs in automated workflows, thereby enhancing work efficiency and data accuracy. It is suitable for developers, business personnel, and trainers who require precise management of time data, helping them achieve complex time calculations and format conversions.

This workflow automates the retrieval and updating of the latest market prices for cryptocurrency portfolios, calculates the total value, and saves the data to Airtable. It runs automatically every hour, ensuring that users stay updated on asset dynamics in real time, while reducing the errors and burden associated with manual updates. By calling the CoinGecko API, the workflow effectively addresses the challenges posed by cryptocurrency price volatility, making it suitable for investors, financial analysts, and any teams or individuals managing crypto assets, thereby enhancing the efficiency and accuracy of data maintenance.

This workflow quickly and batch retrieves customer data from Zoho CRM through a simple manual trigger. Users only need to click the "Execute" button to automatically call the API and pull customer information in real-time, eliminating the cumbersome manual export steps and significantly improving data retrieval efficiency. It is suitable for various roles such as sales, marketing, and customer service, ensuring the timeliness and completeness of data, and supporting the digital transformation of enterprises.

This workflow is manually triggered to automatically access the Hacker Noon website and scrape the titles and links of all secondary headings on the homepage. Users can quickly obtain the latest article information without manually browsing the webpage, enhancing the efficiency of information collection. It is suitable for scenarios such as media monitoring, content aggregation, and data collection, facilitating content analysis and public opinion tracking. This workflow holds significant application value, especially for content editors, market researchers, and developers.

This workflow is mainly used for generating and splitting simulated user data, facilitating subsequent processing. By using custom function nodes, it creates an array containing multiple user information entries and splits them into independent JSON data items. This process addresses the flexibility issues in batch data processing, making it suitable for scenarios such as test data generation, individual operations, and quickly building demonstration data, thereby enhancing the efficiency and controllability of workflow design.