Localize ads - Melius

Localization is one of the bigger time sinks in performance marketing. You launch a campaign in North America, it works, and now it needs to ship to fifteen markets with translated copy, localized cultural cues, and the right units (miles vs km, currency, regional spelling). Done by hand, it’s a multi-week project. Done on Melius, it’s a single brief.

The basic pattern

Open the canvas with your source ad

Either the original asset alone, or the full workflow that produced it. The workflow approach is faster if you’re localizing several variants — you’ll re-run the same workflow with localized prompts.

Group the source ad (and its inputs, if you're keeping the workflow)

Select everything you want localized, hit Cmd+G to group.

Brief the agent

Example:

Take this campaign and generate localized versions for the following markets:
Spain (Spanish), Germany (German), Brazil (Portuguese), France (French),
Japan (Japanese), South Korea (Korean).

For each market: translate all visible copy, adjust units (miles → km
where applicable), and adapt any cultural cues so the ad reads
naturally to a local audience.

Let the agent generate

For each market, the agent creates a new variant. Translation runs through a language model; the localized text gets baked into the new generation.

Review with a native speaker if possible

Translation models are good but not perfect. For markets with high spend, get a quick gut-check from a native speaker — especially for copy with idioms, double meanings, or culturally-specific references.

What the agent handles automatically

The current Melius agent is sophisticated enough that for a well-known brand and market, you don’t need to spell out every localization rule. If you ask for “10 versions of this ad for different regions,” it knows:

To translate copy into the target language
To switch units of measurement (miles ↔ km, °F ↔ °C, $ ↔ local currency)
To swap region-specific cultural references (Thanksgiving → equivalent regional holidays where relevant)
To pick imagery that fits — different model demographics, different settings, different aesthetic norms by region

For more nuanced localization — political sensitivities, regional spelling (UK vs US English), cultural taboos to avoid — be explicit in the prompt.

A worked example

Brand: US-based fitness app. Source ad: static showing a runner with text “Track your miles” and a map of San Francisco. Target: ten markets, full localization. The brief to the agent:

Take @source-ad and localize it for ten markets. For each market:

1. Translate "Track your miles" into the local language, with appropriate
   unit (use km outside the US/UK/Liberia/Myanmar).
2. Replace the San Francisco map with a recognizable city in the target
   market.
3. Update the runner's appearance and setting to feel locally appropriate
   without leaning on stereotypes.
4. Keep the brand palette, typography, and overall composition consistent.

Target markets: UK, Germany, France, Spain, Italy, Brazil, Mexico, Japan,
South Korea, Australia.

The agent generates ten variants on the canvas, each with localized copy, localized map imagery, and localized cultural cues — while keeping the brand’s visual identity consistent.

Working with brand-specific localization rules

Many brands have explicit localization guidelines — what to translate vs leave in English, which markets get full localization vs token translation, region-specific brand voice variants. Put these in your brand anchor:

## Localization rules
- "Track your miles" should always be translated, including unit conversion.
- "[Brand name]" never gets translated.
- Use formal "you" (vous, Sie, ustedes) by default — informal only for Brazil and Mexico.
- Avoid US-specific holidays in any market other than US/UK/AU.

Connect the brand anchor to your localization batch, and the agent will follow the rules across every generated variant.

Sub-regional localization

Some markets are too varied to treat as one localization. The classic case: Miami and rural Texas are both “US,” but the audience, language register, and cultural cues are very different. Same for São Paulo vs Recife in Brazil, or Tokyo vs Osaka in Japan. If the spend justifies it, run sub-regional localization:

For the US market, generate three city-specific variants:
- Miami: include Spanish-language copy alongside English. Beach/tropical setting.
- Austin: laid-back outdoor culture. Casual register.
- NYC: faster pacing, urban setting. Slightly more formal copy.

This is the same pattern as broader localization — just at a tighter granularity. The agent handles it without extra setup.

Common pitfalls

Trusting the translation 100%. Models are good, not perfect. For high-spend markets, native-speaker review is cheap insurance.
Localizing copy but not imagery. Translation alone doesn’t make an ad feel local — the imagery has to land too. Lean on the agent to swap settings, models, and cultural cues, not just words.
Ignoring sub-regional variation in big markets. US, Brazil, India, and a few other markets are too internally varied for a single localization to work everywhere.
Hardcoding brand terms in the brand anchor without translation rules. Your brand anchor should explicitly say what translates and what doesn’t, or the model will guess.

​The basic pattern

​What the agent handles automatically

​A worked example

​Working with brand-specific localization rules

​Sub-regional localization

​Common pitfalls