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This workflow can automatically monitor price changes of multiple e-commerce products at scheduled intervals, capturing and extracting price information in real-time while supporting simultaneous monitoring of multiple products. The system compares the current price with the historical lowest price and automatically sends email notifications in case of price anomalies or price drops, ensuring that users receive timely alerts for the best purchasing opportunities. Through automation, users do not need to manually refresh web pages, significantly improving monitoring efficiency and data accuracy, making it suitable for e-commerce operators and consumers alike.

This workflow is designed to automate the processing of Excel and CSV files, supporting the loading of files from multiple sources and converting them into JSON format for easier data handling. It allows for custom data processing, such as age calculations, and ultimately generates new Excel files, with the option to save the results locally or in the cloud. This process effectively enhances data processing efficiency, reduces errors from manual operations, and is suitable for scenarios such as enterprise customer management, data analysis preprocessing, and file synchronization.

This workflow automatically retrieves product notes, company information, and feature characteristics from the Productboard platform and structurally imports the data into the Snowflake data warehouse. By regularly cleaning and updating the data, it ensures the integrity and timeliness of the information. Additionally, the workflow supports data monitoring, generates weekly update statistics, and sends notifications via Slack, allowing the team to stay informed about the latest product insights, enhance decision-making efficiency, and reduce errors and complexities associated with manual operations.

This workflow automates the daily receipt and aggregation of orders, storing them in an Airtable database, and generates a summary report every evening at 7 PM. Subsequently, a formatted order summary email is sent to the administrators via Gmail, ensuring they are promptly informed of sales performance. This process enhances operational efficiency, eliminates errors in manual aggregation and notifications, and is suitable for business scenarios such as e-commerce and food delivery that require regular order reporting.

This workflow implements the data processing functionality of conditional branching, capable of intelligently selecting the appropriate processing path based on dynamically generated data IDs. By manually triggering execution, the system classifies data with different IDs and assigns different name identifiers, ultimately aggregating or terminating the processing. This design can flexibly respond to diverse business logic, automating the classification and processing of various data, reducing manual intervention, and enhancing work efficiency. It is suitable for scenarios such as automated development and data analysis.

This workflow automatically scrapes company information from the Indeed website using Bright Data's Web Unlocker service. It utilizes the Google Gemini large language model to analyze and intelligently summarize the content, ultimately pushing the structured results to a designated Webhook interface. It effectively addresses issues related to anti-scraping and complex data formats, streamlining the information retrieval process. This solution is applicable in fields such as human resources, market research, and automated development, significantly enhancing data utilization efficiency and business intelligence levels.

This workflow is designed to automate the bulk retrieval of literature entries from Zotero user accounts, supporting the processing of over 100 entries. By using a loop to call the API, it enables automatic pagination requests, eliminating the tedious steps of manual searching and exporting. Additionally, users can flexibly filter and edit literature fields to meet various output requirements. The overall process is efficient and convenient, significantly enhancing the efficiency of literature management and organization, making it particularly suitable for academic researchers and literature management departments.

This workflow automatically parses and validates phone numbers to ensure they are correctly formatted and valid. Through the Uproc service, it accurately identifies international phone numbers, enhancing data quality and reducing manual verification costs. It is suitable for scenarios such as customer information entry, marketing activities, and user registration, helping businesses optimize communication processes, improve operational efficiency, and ensure the validity and availability of phone number information.