This workflow automatically identifies your weekly bestselling product from your Algolia-powered e-commerce store and generates a cinematic product video using Google VEO 3.0 AI, helping marketing teams create engaging video content without manual editing or expensive production tools.
E-commerce stores using Algolia for search. Ideal for marketing teams who want to automate video content creation for top-performing products and maximize conversion potential with engaging visual content.
✅ It DOES:
❌ It DOESN'T:
Think of it as: An automated video production assistant that doubles down on your bestsellers with engaging content, not a full video editing suite.
Setup time: ~20 minutes
ALGOLIA_APP_ID with your Algolia Application IDYOUR_INDEX_NAME with your product index namePROJECT-ID-GOOGLE-CLOUD with your Google Cloud Project IDGOOGLE_STORAGE_BUCKET_NAME with your GCS bucket nameYOUR_SUPABASE_PROJECT with your Supabase project IDYOUR_BUCKET_NAME with your Supabase bucket name[email protected] with your email addresshasVideo, images[], name, description attributeshasVideo, images[], name, description, objectIDVEO 3.0 can only output videos as base64 strings or MP4 files in Google Cloud Storage. Base64 strings are too large for n8n to process (even with code nodes), making Google Cloud Storage mandatory. The workflow then downloads the MP4 and uploads it to Supabase because:
Think of Google Cloud Storage as a temporary staging area required by VEO 3.0's limitations, and Supabase as your actual production storage.
For a typical 6-second product video:
💰 Bottom line: About $0.15-0.30 per video. Running weekly for a year = $8-16 in video generation costs.
Customize the video prompt: The default prompt creates a cinematic studio dolly shot. Edit the jsonBody in "Generate video with Google VEO 3" to match your brand style (fast-paced, minimalist, lifestyle, etc.).
Adjust bestseller logic: Modify the Algolia query to add filters like category:electronics or brand:Nike to focus on specific product segments.
Use manual execution during setup: Don't wait until Monday! Run the workflow manually to catch configuration issues like broken image URLs or missing credentials immediately.
Monitor your email alerts: If you frequently get "no image" or "broken image" alerts, audit your product data quality in Algolia. Missing images = lost video opportunities.
Start with test products: Before going live, manually trigger the workflow on a product you know has good images. Verify the video appears correctly in your Supabase bucket and Algolia record.
Check your GCS bucket occasionally: Videos accumulate in Google Cloud Storage after each run. Set up a lifecycle policy to auto-delete files older than 7 days to avoid unnecessary storage costs.
Adjust the schedule: If Monday 9PM doesn't work for your team's workflow, change the trigger to run on a different day or time that aligns with your content calendar.
This workflow leverages Algolia's custom ranking feature. When you send an empty search query to Algolia, the first result returned follows your custom ranking criteria. This is an Algolia best practice that ensures your most relevant products appear first even without search terms.
In the example configuration, custom ranking uses:
inStock attribute - Prioritizes available productspopularity attribute - A computed metric based on sales volume, views, and other signalsYou'll need to configure your own custom ranking in your Algolia index settings to match your business criteria. The workflow assumes your index is already configured to return your bestselling product first when queried with no search terms.