Overview
This workflow automates the monitoring and management of online advertisements using advanced AI models such as GPT-4 and Gemini. It streamlines the process from ad data collection to media handling and storage.
Key Features
- Manual Trigger: Initiate the workflow on demand for flexible monitoring.
- AI-Powered Filtering: Uses switch and filter nodes to identify ads with high engagement (e.g., likes).
- Media Processing: Downloads ad videos and uploads them to Google Drive for centralized storage.
- Ad Library Scraping: Integrates with an ad library scraper to extract and analyze image ads in batches.
- Automated Waiting and Batching: Employs wait and splitInBatches nodes to optimize processing and avoid rate limits.
Benefits
- Efficiency: Reduces manual effort in tracking and managing ad assets.
- Centralized Storage: Ensures all relevant media is securely stored and easily accessible in Google Drive.
- Scalability: Handles large volumes of ads and media through batching and automation.
- AI Insights: Leverages AI models for smarter ad selection and analysis.
Use Cases
- Marketing teams monitoring competitor ads.
- Agencies managing multiple ad campaigns.
- Businesses seeking automated ad asset archiving and analysis.
Integrations
- Google Drive for media storage.
- HTTP Requests for data retrieval and ad scraping.
- AI Models (GPT-4, Gemini) for intelligent filtering.
