Analyze Meta ads creatives with Google Vision & Video Intelligence APIs

This workflow transforms your Meta Ads creatives into a rich dataset of actionable insights. It's designed for data-driven marketers, performance agencies, and analysts who want to move beyond basic metrics and understand the specific visual and textual elements that drive ad performance. By automatically analyzing every video and image with Google's powerful AI (Video Intelligence and Vision APIs), it systematically deconstructs your creatives into labeled data, ready for correlation with campaign results.

Use Case You know some ads perform better than others, but do you know why? Is it the presence of a person, a specific object, the on-screen text, or the spoken words in a video? Answering these questions manually is nearly impossible at scale. This workflow automates the deep analysis process, allowing you to: Automate Creative Analysis: Stop guessing and start making data-backed decisions about your creative strategy. Uncover Hidden Performance Drivers: Identify which objects, themes, text, or spoken phrases correlate with higher engagement and conversions. Build a Structured Creative Database: Create a detailed, searchable log of every element within your ads for long-term analysis and trend-spotting. Save Countless Hours: Eliminate the tedious manual process of watching, tagging, and logging creative assets.

How it Works

The workflow is triggered on a schedule and follows a clear, structured path:

1. Configuration & Ad Ingestion: The workflow begins on a schedule (e.g., weekly on Monday at 10 AM). It starts by fetching all active ads from a specific Meta Ads Campaign, which you define in the Set Campaign ID node.

2. Intelligent Branching (Video vs. Image): An IF node inspects each creative to determine its type. Video creatives are routed to the Google Video Intelligence API pipeline. Image creatives are routed to the Google Vision API pipeline.

3. The Video Analysis Pipeline: For each video, the workflow gets a direct source URL, downloads the file, and converts it to a Base64 string. It then initiates an asynchronous analysis job in the Google Video Intelligence API, requesting LABELDETECTION, SPEECHTRANSCRIPTION, and TEXTDETECTION. A loop with a wait timer periodically checks the job status until the analysis is complete. Finally, a Code node parses the complex JSON response, structuring the annotations (like detected objects with timestamps or full speech transcripts) into clean rows.

4. The Image Analysis Pipeline: For each image, the file is downloaded, converted to Base64, and sent to the Google Vision API. It requests a wide range of features, including label, text, logo, and object detection. A Code node parses the response and formats the annotations into a standardized structure.