Daily USD Exchange Rate Auto-Update and Archiving Workflow

This workflow simplifies XML data processing by automatically parsing and converting predefined XML string data through a manual trigger function. Utilizing built-in XML nodes, it quickly transforms XML formatted data into an easily manageable structured format, reducing the technical barriers for data processing and improving work efficiency. It is suitable for automation engineers, business analysts, and any users who need to handle XML data, supporting automated business processes and system integration.

This workflow is designed to automatically monitor product prices on the Zalando e-commerce platform. It periodically fetches and parses product information to update the latest prices in Google Sheets and records price history. When the price falls below a user-defined alert value, the system automatically sends an email notification, helping users seize shopping opportunities in a timely manner, saving time and effort. It is suitable for e-commerce shoppers, operations personnel, and data analysts.

This workflow can automatically read the sitemap.xml file of a website and convert its XML data into JSON format, extracting all URL entries. Users can quickly filter the links that meet their criteria based on custom filtering conditions, such as links to documents ending with .pdf. This process significantly enhances the efficiency of sitemap data processing, allowing users to quickly access specific types of resources, making it suitable for various scenarios such as SEO optimization, content management, and data analysis.

This workflow efficiently scrapes historical novel book information from designated book websites through automation. It utilizes AI models to accurately extract key information such as book titles, prices, stock status, images, and purchase links, and then structures and saves this data in Google Sheets. It addresses the issues of disorder and inconsistent formatting in traditional data collection, significantly enhancing data accuracy and organization efficiency, making it suitable for users in e-commerce operations, data analysis, and content management.

This workflow is designed to automate the processing of pandemic-related data. It can download CSV files from a specified URL, filter out the pandemic testing data for the DACH region (Germany, Austria, Switzerland) in 2023, and intelligently import it into Google Sheets. By automatically triggering matches with unique data keys, it significantly reduces the manual work of downloading and organizing data, enhancing the speed and accuracy of data updates. It is suitable for use by public health monitoring, research institutions, and data analysts.

This workflow automatically scrapes the information of the top 13 trending code repositories from GitHub's trending page for today, including data such as author, name, description, programming language, and links, generating a structured list in real-time. By automating the process, it addresses the cumbersome task of manually organizing data, improving the speed and accuracy of information retrieval. This helps developers, product managers, and content creators quickly grasp the latest dynamics of open-source projects, supporting industry technology trend tracking and data analysis.

This workflow automatically retrieves official company information from the SIREN business database by calling the API of the National Institute of Statistics and Economic Studies of France. It intelligently enriches and updates company data in Agile CRM. It ensures the accuracy of the company's registered address and unique identification code (SIREN), addressing issues of incomplete and outdated company data, significantly enhancing data quality and work efficiency. This makes it particularly suitable for sales and customer management teams that need to maintain accurate customer profiles.

This workflow is designed to automatically sync payment data from the Stripe platform to HubSpot contact records, ensuring that the cumulative spending amount of customers is updated in real-time. Through scheduled triggers and API calls, the workflow efficiently retrieves and processes customer and payment information, avoiding duplicate queries and improving data accuracy. This process not only saves time on manual operations but also provides the sales and customer service teams with a more comprehensive view of customer value, facilitating precise marketing and customer management.