Localize campaign

Take one finished campaign and adapt it to N markets — translated copy, culturally appropriate visuals, right-to-left handling for AR/HE, and text-expansion-safe layouts. Built for consistency (same campaign identity per market) and speed (one batch per locale).

When to Use

User has a shipped campaign in one market and needs to launch across 3+ additional locales.
"Localize across DE, FR, JP, BR, ES" / "translate + adapt creatives per market" / "RTL version for AR".
Master campaign has on-image text, people, or cultural motifs that need swapping per locale.
Do NOT use for pure text translation (use an LLM directly) or for a fresh campaign (use
```
marketer-campaign-kit
```
first, then this skill).

Prerequisites

Ask up front if the brief doesn't cover it (combine into one message):

Master campaign assets — paths/URLs to the approved creative. What's already finalized (hero, ad variants, email, LP)?
Target locales — language + region (e.g.
```
de-DE
```
,
```
fr-FR
```
,
```
ja-JP
```
,
```
ar-SA
```
,
```
pt-BR
```
). Region matters for cultural appropriateness.
Translated copy — is it done? If yes, paste it. If no, note which copywriter/vendor owns it (don't auto-translate ad copy — compliance risk).
Cultural swaps needed — people (face/ethnicity), settings (interior style, streetscape), props (food, gestures)? If the hero has a specific person, does that persist or get replaced per locale?
RTL locales in scope — Arabic, Hebrew, Farsi? Layout needs to mirror, text extends right-to-left.
Deliverable naming — ad-platform uploaders expect
```
{campaign}_{locale}_{size}.webp
```
.

Never auto-translate ad copy without a reviewer — legal/compliance owns sign-off.

How to Run

Inventory the master assets. List every creative that needs localizing (hero, 6 ad variants, email, LP hero = 9 per locale × 5 locales = 45 assets).
Collect translated copy per locale BEFORE generating. Don't batch-run with English placeholders — you'll re-render everything.
Choose adaptation strategy per asset:
- Text-only change (headline on a clean bg): use
```
ideogram-v3
```
  with the translated copy and same visual.
- In-place motif swap (person, setting): use an edit model (
```
qwen-image-edit-plus
```
  ,
```
flux-kontext-pro
```
  ) with the original image + a locale-specific prompt.
- Full regeneration (complex cultural swap): generate fresh from the original prompt + locale guidance, referencing the original as
```
image
```
  for composition.
Write per-locale manifests. One manifest per locale keeps naming clean and lets you parallelize across locales without collision.

Estimate per locale.

bash

gen-ai batch run localize-de.json --dry-run

Run locales in sequence, not in parallel. Review one locale's output end-to-end before kicking off the next — catching a cultural mismatch in DE means fixing the prompt before JP, FR, and BR inherit it.
bash
```
gen-ai batch run localize-de.json -c 4 -o ./out/de-DE
```
Review with a native speaker per locale. Every locale. No exceptions. Especially for JP (text rendering), AR (RTL + text), and any market with a dedicated country manager.
Package and hand off. Folder per locale, filename includes locale code,
```
results.json
```
archived for audit.

Quick Reference

One manifest per locale keeps things tidy.

{locale}

and

{name}

placeholders support cross-locale reuse.

json

{
  "defaults": {
    "model": "qwen-image-edit-plus",
    "imageUrls": ["https://cdn-pipeline-output.picsart.com/.../master-hero.webp"],
    "negativePrompt": "low quality, watermark, culturally inappropriate"
  },
  "jobs": [
    { "id": "hero_de-DE",        "prompt": "adapt hero for German market — preserve composition, swap setting to central-European urban, replace overlay text with: \"Jetzt entdecken\"",                     "aspectRatio": "16:9" },
    { "id": "ad_9x16_de-DE",     "prompt": "adapt ad for German market — keep product/subject, swap scene to Berlin street, overlay headline: \"Jetzt entdecken — 20% Rabatt\"",                          "aspectRatio": "9:16" },
    { "id": "ad_1x1_de-DE",      "prompt": "adapt ad for German market — clean background, German headline: \"Jetzt entdecken\", CTA: \"Mehr erfahren\"",                                                  "aspectRatio": "1:1"  },
    { "id": "email_de-DE",       "prompt": "email header for German launch — German copy on-canvas: \"Jetzt entdecken\"",                                                                                   "aspectRatio": "3:1"  },
    { "id": "lp_hero_de-DE",     "prompt": "LP hero for German market — same product, German subtitle: \"Entdecken Sie die neue Kollektion\"",                                                              "aspectRatio": "16:9" }
  ]
}

For RTL locales (AR, HE), mirror layouts explicitly in the prompt: "right-to-left layout, headline reads from right, mirror the hero composition".

For voiceover localization (video campaigns), pair with

gen-ai generate -m eleven-multilingual-v2

per locale — keep

voice

ID consistent across locales for brand continuity.

Quick Reference

Sub-task	Model	Why
In-place text swap on clean bg	`ideogram-v3`	Only model that reliably renders legible text in multiple scripts (Latin, Cyrillic, JP, AR)
Motif / setting swap, preserve subject	`qwen-image-edit-plus`	Strong at in-place edits — keeps composition, swaps scene
Instructed edits with reference	`flux-kontext-pro`	Precise edit-to-prompt adherence, good when you need surgical changes
Full regeneration with cultural guidance	`flux-2-pro`	Best photoreal; reference the original as `image` to keep composition
Face/person swap with identity consistency	`gemini-3-pro-image` (Nano Banana Pro)	Best at persisting or deliberately swapping a subject across renders
Multilingual voiceover	`eleven-multilingual-v2`	Consistent voice across locales — set `voice` ID in `defaults`
Background replacement only	`gen-ai change-bg` (subcommand)	Pixel-identical subject, locale-appropriate scene

Confirm IDs with

gen-ai models

Procedure

Text expansion is real. German runs 30% longer than English, French 20% longer, JP/ZH 30% shorter but character-dense. Leave 25-30% breathing room in text-safe zones before rendering.
Never auto-translate ad copy. Compliance owns sign-off. Collect human-reviewed translations, then render.
RTL locales mirror the layout. AR/HE need hero composition flipped and headline-reads-right. State it explicitly in the prompt.
Culturally appropriate faces/settings. A Berlin scene feels wrong in Tokyo. If the master has a person, decide early: persist (identity consistency via Nano Banana Pro) or swap per market.
ideogram-v3
is the only reliable option for on-image text in non-Latin scripts. Other models render JP/AR/KR as gibberish. Use it for any text-bearing asset.
One locale at a time, reviewed end-to-end. Parallelizing 5 locales hides prompt bugs until you've spent 5x the credits.
Native-speaker review is non-negotiable. LLMs miss cultural nuance. Every locale gets eyes on from someone in-market before shipping.
Filename locale codes enable direct ad-platform upload.
```
launch_de-DE_9x16.webp
```
parses cleanly in Meta / Google / TikTok CSV importers.
Keep voice ID consistent across multilingual VO. Same voice across markets = brand continuity. Set
```
voice
```
in
```
defaults
```
, not per-job.

Pitfalls

Text overflowing the safe zone in DE / RU / FI. Copy expansion wasn't accounted for in the master layout — leave 25-30% margin before localizing.
JP / AR / KR text renders as gibberish. Wrong model. Use
```
ideogram-v3
```
for any non-Latin on-image text, not flux/recraft.
RTL layout not mirrored. Arabic users get a headline that reads wrong direction + hero composition that feels wrong. Explicit mirror instruction fixes it.
Culturally tone-deaf imagery. A Christmas-themed visual in a Muslim-majority market, a left-hand gesture in SEA — run cultural review per market.
Translating in the prompt with the LLM. Ad copy goes through compliance; don't have the model "translate this headline to German" mid-prompt. Use human-reviewed translations.
Parallelizing all 5 locales upfront. One prompt bug becomes 5 locales of wasted credits. Sequence them; review DE, then kick off FR.
Inconsistent voice across locales in VO. Different
```
voice
```
IDs per locale breaks brand continuity — set one voice ID across all TTS jobs.
Skipping native-speaker review. "The model did fine on German last time" is how you ship a mistranslation.

Verification

Run

gen-ai whoami

to confirm authentication, then re-run the failed command with

--debug

Cost & time

Rough estimate to localize a 9-asset campaign across 5 locales (45 total renders):

Asset type	Count per locale	Model	Credits each	Per locale	5 locales
Hero + ad + email + LP (motif swap)	5	`qwen-image-edit-plus`	~2	10	50
Text-bearing assets (headlines, CTAs)	4	`ideogram-v3`	~3	12	60
Image subtotal	9			~22	~110 credits
Voiceover (if video campaign)	1 per locale	`eleven-multilingual-v2`	~1-3	~2	~10
Grand total					~120 credits
Wall time (sequential per locale, concurrency 4 within)				~3 min	~15 min

Full regeneration via

flux-2-pro

roughly doubles the image credits. Estimate explicitly with

gen-ai batch run localize-{locale}.json --dry-run

before spending.

marketer-localize-campaign

NPX Install

Tags

SKILL.md Content

Localize campaign

When to Use

Prerequisites

How to Run

Quick Reference

Quick Reference

Procedure

Pitfalls

Verification

Cost & time

See also