Intelligent Hydration Reminder and Tracking Workflow

This workflow automatically reads YouTube video links from Google Sheets, captures comment data in real-time, and uses an AI model to perform sentiment analysis on the comments, classifying them as positive, neutral, or negative. The analysis results are updated back to Google Sheets, ensuring consistency and timeliness in data management. By supporting pagination for comment retrieval and allowing flexible update frequencies, it greatly enhances the ability of content creators and brand teams to gain insights into audience feedback, helping to optimize content strategies and market responses.

This workflow automatically renames specified key names in a set of initial data through a manual trigger function, helping users quickly achieve data field conversion and standardization. It is suitable for use in scenarios such as development debugging and data preprocessing, effectively addressing the issue of inconsistent field naming. This reduces the tediousness of manual modifications, enhances the efficiency and accuracy of data organization, and facilitates the use of subsequent processes.

This workflow automatically processes nested lists by receiving data from external POST requests, generates Excel format spreadsheet files, and directly returns them to the requester. It aims to quickly convert complex API data into an easily viewable and analyzable format, addressing the cumbersome issues of manual organization and format conversion. It is suitable for developers, analysts, and business scenarios that require automated data export, thereby improving work efficiency.

This workflow integrates multiple APIs from CoinMarketCap to create an intelligent agent tool that helps users conduct in-depth queries and analyses of cryptocurrency exchange information and market sentiment. It supports multi-dimensional data retrieval, including exchange details, asset status, and the Fear and Greed Index. By incorporating the GPT-4o Mini model, it enables natural language interaction, enhancing the efficiency and accuracy of data acquisition while lowering the barrier for users to access key information. It is suitable for investors, analysts, and community operators.

This workflow can automatically scrape content from multi-page websites, supporting the retrieval of all site page links through sitemap.xml. It intelligently filters web pages based on specified themes or keywords, extracting titles and the main content in Markdown format. The results are saved to Google Drive for unified management and archiving. It simplifies the traditional web scraping process, eliminating the need for API keys, making it suitable for various scenarios such as content operations, data analysis, and market research. This enhances information collection efficiency and lowers the technical barrier.

This workflow is manually triggered to automatically retrieve customer information from the customer data storage system and securely send each customer's name to a designated Webhook interface via HTTP POST requests, enabling fast batch transmission. It addresses the challenges of obtaining and securely transmitting customer information, making it suitable for scenarios that require regular synchronization of customer data. This enhances data processing efficiency and security, particularly benefiting teams in marketing, customer service, and data analysis.

This workflow automatically retrieves company data from Google Sheets, uses web scraping technology to gather content from the company's official website, and employs AI for intelligent analysis to extract structured information. Ultimately, it writes the enriched data back to Google Sheets. This process significantly enhances the completeness and accuracy of corporate information, addressing the inefficiencies of traditional data collection. It is applicable in various scenarios such as market research, sales management, and data analysis, helping users quickly obtain high-quality business insights and improve decision-making efficiency.

This workflow can be manually triggered to quickly batch retrieve all product information from a Shopify store, enabling automated data extraction. The operation is simple; just click to execute without the need for coding. It is suitable for e-commerce operators, data analysts, and marketing teams, enhancing the efficiency and accuracy of obtaining product information, and supporting subsequent business decisions and data-driven operations.