CONTENT CREATION

Airtable campaign fan-out with per-channel image variants

Reads a campaign brief row from Airtable, expands a single blog draft into localized copy plus channel-sized image variants.

CategoryContent Creation
Enginesim
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerAirtable campaign brief marked ApprovedAirtableAirtable
  • ActionRead linked draft, channels, and localesAirtableAirtable
  • ActionGenerate localized per-channel copyOpenAI
  • ActionRender channel-sized image variantsImage generation
  • LogicPair copy with images, drop incomplete sets
  • OutputWrite assets back as linked Airtable recordsAirtableAirtable

What it does

Given a campaign brief in Airtable that points at a blog draft and lists target channels and locales, this workflow produces a matrix of assets — localized copy for every channel crossed with correctly sized image variants — and writes each combination back to Airtable as its own linked, ready-to-schedule record.

When to use it

You plan campaigns in Airtable and need one source draft fanned out into dozens of channel-by-locale assets, each tracked as a discrete record your team can schedule and report on individually.

How it works

  1. 1A new or updated Airtable campaign brief marked Approved fires the trigger.
  2. 2The linked blog draft and the brief's channel and locale lists are read from Airtable.
  3. 3OpenAI generates localized copy tailored to each channel in the matrix.
  4. 4A generate-image step renders image variants sized for each channel.
  5. 5A logic step pairs every copy variant with its matching image and drops incomplete combinations.
  6. 6Each completed asset is written back to Airtable as a linked record tied to the campaign.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect Image generationManaged Nano Banana image renders, metered per image.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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