MARKETING

Localized Ad Creatives per Region from a Product Feed

Reads new products from a Postgres feed, generates region-specific image variants with localized overlays, stores them in S3.

CategoryMarketing
Enginesim
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew product row in Postgres feedPostgreSQLPostgres
  • LogicExpand product across target regions
  • ActionGenerate localized variant per region on ReplicateReplicateReplicate
  • ActionUpload rendered assets to S3 by region and SKUAWS S3
  • OutputCatalog each variant in the Airtable asset libraryAirtableAirtable

What it does

Produces market-specific ad creatives at scale. For each new product, it generates image variants tuned to each target region's style and language overlay, stores the rendered assets in cloud storage, and catalogs them so regional teams can grab the right creative.

When to use it

Use it when you sell into multiple markets and need localized visuals rather than one generic creative. Ideal for ecommerce and DTC brands launching products across regions where imagery and on-image copy must differ.

How it works

  1. 1A new product row inserted in the Postgres product feed fires the trigger.
  2. 2The workflow expands the product across your configured target regions.
  3. 3For each region, Replicate generates a localized image variant using the region's style preset and language overlay.
  4. 4Each rendered asset is uploaded to an S3 bucket organized by region and SKU.
  5. 5An Airtable asset-library row is created per variant with the S3 link, region, and product reference.
  6. 6The final catalog is ready for regional teams to pull into their own ad pushes.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect ReplicateImage, video, and model inference.
  3. 3
    Connect AWS S3Buckets, objects, signed URLs.
  4. 4
    Connect AirtableBases, tables, views, automations.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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