A senior campaign manager at a pan-European retailer once calculated that localising one campaign for five markets took 23 working days on average. That included translation, local adaptation, legal review, and final approval from each market's team. By the time every market had signed off, the campaign moment had often passed. Here's how teams are compressing that to a single day.
The difference between translation and localisation
Translation swaps words. Localisation changes the message to fit a different context. A campaign headline that resonates in the Netherlands may fall flat in Spain, not because of language, but because the cultural reference, the humour, or the assumed context doesn't travel.
When briefing AI for localisation, you need to specify both layers. For each market:
- Target language and regional dialect (Spanish for Spain vs. Latin America are different briefs)
- Cultural constraints, what humour, imagery, or references to avoid
- Local regulations, especially for financial, health, or legal claims
- Any local competitors or market context the copy should acknowledge
- Whether the campaign is adapting an existing concept or building local-first
Build a master brief, then branch it
The most efficient localisation workflow starts with one master brief that contains the campaign core: the central message, the offer, the creative concept, the visual direction. Everything that doesn't change by market.
Then you layer market-specific parameters on top: language, local examples, tone adjustments, format specs (some social platforms have different character limits and conventions by country), and any legal overlays.
When this branching structure is built into your workflow template, generating five market versions is running the workflow five times with different parameter sets, not starting from scratch five times. Brands like Bol.com managing multilingual markets build this kind of template infrastructure precisely to avoid re-doing work per campaign.
What still needs a human in the loop
Localisation at speed does not mean localisation without review. Three things require human sign-off regardless of how good the AI output is:
- Claims and compliance: Any regulated claim needs a local legal or compliance reviewer. AI can draft; it cannot self-certify.
- Cultural sensitivity: A local native speaker should check the final copy for unintended connotations. This takes 20 minutes per market if the draft is already solid.
- Brand voice accuracy: Does this sound like your brand in German, not just grammatically correct German? This is a judgment call that requires someone who knows both the brand and the market.
Build these review steps into the workflow rather than bolting them on at the end. A 20-minute local review before final approval is not a bottleneck, it's a safeguard that prevents a public correction.
Image and visual localisation
Copy is only half the job. Visuals need localisation too. A product image that shows a UK kitchen won't land in Germany. An image featuring a specific season may be off-cycle in a southern market. Specify visual localisation requirements explicitly: seasonal accuracy, representation, colour associations that differ by market (white is associated with mourning in some Asian markets, for example).
If you're producing images through an AI workflow, store market-specific image parameters alongside your copy parameters. This way, a 'Netherlands campaign' template automatically applies Dutch visual conventions without needing a separate brief for the design team.
Choose your two most time-consuming markets to localise and build a template for them first. Run one real campaign through the template. Note every place where you had to manually correct something. Add those corrections to the template parameters. By the second campaign, your manual correction rate should be half what it was, and the time to publish should be measurable in hours.
Further reading
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