I'm building a localization system for product, marketing, and help docs

Great use case. A localization system for product, marketing, and help docs usually works best when it’s designed around content types, workflow, and reuse rather than just translation.

Here’s a solid starting structure:

1) Separate content by domain

Treat these as different localization tracks:

• Product UI: short strings, strict length limits, context-sensitive, high release velocity
• Marketing: brand tone, locale adaptation, campaign-specific language
• Help docs: long-form content, screenshots, frequent updates, glossary consistency

Each should share terminology, but not necessarily the same workflow.

2) Use a source-of-truth content model

Store content with:

• stable IDs / keys
• source locale
• content type
• context metadata
• audience
• platform/channel
• glossary terms
• screenshots or reference notes where relevant

Example metadata:

{
  "id": "checkout.pay_button",
  "type": "ui_string",
  "sourceLocale": "en-US",
  "context": "Button in checkout flow",
  "maxLength": 20,
  "productArea": "Payments",
  "tone": "clear, concise"
}

3) Build translation memory and glossary first

These are the biggest leverage points:

• Translation memory: reuse previously translated segments
• Glossary / termbase: enforce preferred translations for product names, feature names, legal terms, and key phrases
• Style guide: tone, formality, punctuation, capitalization, brand rules

For help docs and marketing, glossary consistency is especially important.

4) Add context to reduce translation errors

Translators/localizers need:

• screenshots
• character limits
• surrounding text
• where the text appears
• whether placeholders are dynamic
• notes for ambiguous terms

Example:

• “Save” = button text?
• “Save” = verb in a sentence?
• “Save changes” = confirmation action?

5) Use different workflows per content type

A practical workflow split:

Product UI

• source text in code or structured content
• automated extraction
• translation review
• QA checks for truncation, placeholders, ICU messages, RTL support

Marketing

• copywriting/localization adaptation
• human review by in-market linguist
• optional transcreation
• approvals from brand/legal

Help docs

• content chunks or markdown blocks
• translation memory-heavy
• screenshots and links managed carefully
• scheduled retranslation when product changes

6) Design for localization-friendly authoring

Encourage source content that is easy to localize:

• no hardcoded strings in code
• avoid concatenation like Hello " + name
• use ICU messages for plurals and gender
• keep sentences self-contained
• avoid cultural references unless intentional
• minimize embedded formatting complexity

7) Plan for locale-specific adaptation

Not all content should be translated literally. You may need:

• date/time/number/currency formatting
• plural rules
• unit conversion
• region-specific legal copy
• different imagery or examples
• right-to-left layout support

8) Include quality controls

Recommended checks:

• missing translations
• stale translations after source edits
• placeholder mismatches
• length overflow
• terminology violations
• broken links
• RTL rendering issues
• encoding and punctuation issues

9) Decide your system architecture

Common approach:

• CMS or content platform for docs/marketing
• i18n framework for product strings
• TMS (translation management system) or translation pipeline connecting both
• review UI for linguists, product managers, and legal/brand reviewers

10) Think about versioning and release management

You’ll want:

• source content versioning
• locale versioning
• translation status per key/chunk
• approval states
• rollback support
• release gating for critical locales

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If you want, I can help you with any of these next:

1. a data model/schema for localization content
2. a workflow diagram for product/marketing/help docs
3. a recommended tech stack
4. a process for translation memory, glossary, and QA
5. a MVP architecture for building this from scratch