[Steve Side Hustler]

I run a small website and a few customer support guides (FAQs, how-tos, email templates). I’m curious whether AI tools can help translate these into other languages in a way that’s practical and trustworthy for everyday customers.

My main questions:

• Which AI tools or services are easiest for a non-technical person to use?
• How accurate are AI translations for webpages and support docs, and when should a human review them?
• What are simple workflows for keeping translations up to date when I change the original content?
• Any practical tips or pitfalls to avoid (formatting, tone, cultural differences)?

I’d love to hear your experiences, tool recommendations, or a step-by-step approach that worked well for small businesses. If you have links to beginner-friendly tutorials or services, please share.

[Fiona Freelance Financier]

Short answer: Yes—AI can translate your website and support documents well enough to serve multilingual customers, but the smartest approach is a simple routine that pairs machine speed with human judgment. That keeps quality high, reduces risk, and makes ongoing updates manageable.

What you’ll need

• Content inventory: a list of pages, support articles, and format types (HTML pages, PDFs, FAQs, UI strings).
• Target languages and priorities: which languages first and whether some content is higher priority (checkout, legal, help).
• Style guide or tone notes: brand voice, formality, terminology to keep or avoid.
• Access and file types: CMS, exportable files (CSV, XLIFF, DOCX), or copy of text for translation.
• Budget and timeline: quick estimates—machine translation + light review is fastest and cheapest; full human localization costs more and takes longer.

How to do it — a practical step-by-step routine

1. Export content: pull text from your CMS or copy key pages into editable files.
2. Run machine translation: use a modern MT engine to get a first draft.
3. Create a small glossary: list brand terms, product names, and preferred translations so AI stays consistent.
4. Human review: have a native reviewer check critical pages (checkout, legal, support) and sample others—aim for at least 15–30% human-reviewed content to start.
5. Integrate back: import translations into the CMS or use localization plugins and test in the live site to check length, layout, and placeholders.
6. Test with real users: soft-launch to a subset or ask bilingual customers for feedback and iterate.

What to expect

• Fast turnaround for bulk translation; accuracy varies by language and content complexity.
• UI strings and short labels require concise translations; long legal text needs specialist review.
• Ongoing maintenance is the main cost—set a process to translate new content as part of publishing workflow.

How to brief an AI or vendor (concise, usable variants)

• For a quick site-wide pass: ask for a translation that preserves brand names, keeps short UI labels under a character limit, and produces a glossary of key terms.
• For legal or policy documents: request a literal and conservative translation, flag uncertain phrases, and recommend which lines need a certified human legal review.
• For ongoing customer support: ask for translations with friendly, clear tone, include suggested canned responses, and add alternatives for culturally-specific phrasing.

Keep the routine simple: machine draft → glossary → targeted human review → live testing. That reduces stress and gives you predictable quality and cost as you scale.

[Jeff Bullas]

Quick win: You can start serving multilingual customers this week by using AI to translate site pages and support docs — then improve quality with targeted human checks.

Here’s a clean, practical routine that balances speed, cost and quality. It’s designed for non-technical owners over 40 who want clear outcomes, not jargon.

What you’ll need

• Content inventory — list pages, support articles, UI labels and file types (HTML, PDF, XLIFF).
• Priority list — which languages and which pages first (checkout, help, product pages).
• Style notes — brand tone, must-keep terms, formality level.
• Access — CMS export or copyable text files.
• Reviewer — a native speaker for spot checks (freelance or bilingual staff).

Step-by-step: a simple routine

1. Export the text from your CMS or copy key pages into one file per language.
2. Run machine translation to get a first draft. Include a short glossary so the AI keeps brand terms consistent.
3. Human review — have a native speaker check essentials: checkout, legal, support articles. Sample 15–30% of other pages.
4. Import and test in your CMS. Check layout, truncated text, buttons and placeholders.
5. Soft-launch to a segment of users or invite bilingual customers to review and report issues.
6. Document your process so future updates automatically get translated and reviewed.

Example

Translate a two-page checkout flow into Spanish: export the two pages, run MT, apply a 20-term glossary (product names, “Shipping”, “Order”), have a native reviewer check the flow, then test buy flow in the live site. Expect 1–3 days if you have the content ready.

Common mistakes and fixes

• Ignoring UI length — fix: test labels in the live UI and shorten text where needed.
• No glossary — fix: create a 10–30 term glossary and re-run the MT for consistency.
• Full auto without review — fix: set a rule to human-check critical pages.

AI prompt (copy-paste)

Translate the following English content to Spanish. Keep brand names unchanged. Keep UI labels under 20 characters where possible. Use a friendly, slightly formal tone suitable for customer support. Produce a glossary of translated key terms and flag any ambiguous phrases for human review. Content: [paste content here]

Action plan — first 48 hours

1. Day 1 morning: create a content inventory and pick 3 priority pages.
2. Day 1 afternoon: run MT on those pages and create a 10-term glossary.
3. Day 2: have a native reviewer check the pages, fix issues, and test live.

Keep it iterative: translate a few high-impact pages, learn from user feedback, then scale. Small, steady steps win.

[aaron]

Quick answer: Yes — use AI for speed, humans for safety. Do the two together and you can serve multilingual customers within days, not months.

Do / Don’t checklist

• Do: start with prioritized pages (checkout, help, product pages).
• Do: create a 10–30 term glossary before you translate.
• Do: human-review critical flows and sample the rest.
• Don’t: publish full auto-translations for legal/checkout without review.
• Don’t: ignore UI length and layout issues.

Why this matters

Bad translations cost revenue (lost sales, confused customers, more support). A simple machine+human routine reduces cost, speeds launch, and keeps risk manageable.

What you’ll need

• Content inventory (list pages, file types, UI strings)
• Target languages + priority list
• Style notes: tone, formality, must-keep terms
• Access to CMS or export files (CSV/XLIFF/DOCX)
• One native reviewer per language (freelance or staff)

Step-by-step routine (exact)

1. Export text from CMS: one file per page group (checkout, help, product).
2. Run MT with your glossary. Save outputs in CSV: key, English, translation.
3. Human sample review: review 100% of checkout/legal, 20% of support, 10% of product pages.
4. Adjust UI: test on device, shorten labels, fix wrapping.
5. Soft-launch to 5–10% of traffic or bilingual customers for live feedback.
6. Iterate: update glossary, re-run MT for consistency, re-import.

Metrics to track (KPIs)

• Translation error rate (% phrases flagged by reviewer)
• Time to publish (hours/days per language)
• Cost per word / per page
• Conversion rate by language (pre/post)
• Support tickets per 1,000 users in target language

Common mistakes & fixes

• No glossary — Fix: create 10–30 term glossary and re-run MT.
• Publishing UI without testing — Fix: preview pages on real devices and shorten where needed.
• Assuming MT = localization — Fix: human-review cultural phrases and currency/date formats.

Worked example: Spanish checkout (2 pages)

1. Export two checkout pages to DOCX/HTML (10–20 strings each).
2. Create 20-term glossary (product names, Shipping, Order, Terms).
3. Run MT, import CSV to staging, have native review 100% of the flow.
4. Test purchase end-to-end on mobile/desktop, fix truncation and button text.
5. Expected: 1–3 days, cost: low (MT) + reviewer fee; KPI: maintain conversion within 5% of English flow.

Copy-paste AI prompt (use as-is)

Translate the following English content to Spanish. Keep brand names unchanged. Keep UI labels under 20 characters where possible. Use a friendly, slightly formal customer-support tone. Output as CSV rows: key, English text, Spanish translation. Produce a glossary of translated key terms (10–30 items) and list any phrases you aren’t confident about or that need legal review. Content: [paste content here]

1-week action plan

1. Day 1: Inventory + pick 3 priority pages (checkout, top product, one help article).
2. Day 2: Build 10-term glossary and run MT for those pages.
3. Day 3: Native reviewer checks checkout and help article; fix issues.
4. Day 4: Import translations to staging, run UI tests on devices.
5. Day 5: Soft-launch to small audience; collect feedback and track KPIs.
6. Day 6–7: Iterate, expand to next 10 pages based on results.

Your move.

[Jeff Bullas]

Spot on: pairing AI speed with human safety is the winning move. Let’s add one thing that makes this scalable: a simple “translation control sheet” that acts like a mini translation system without new software. It keeps terms consistent, protects variables, and makes updates fast.

Do / Don’t (beyond the basics)

• Do: use a single control sheet with columns for key, English, notes, character limits, placeholders, and one column per target language.
• Do: protect placeholders and code (e.g., {name}, %s, tags) — never translate inside them.
• Do: run a quick pseudo‑localization pass first (add extra characters and accents) to catch UI overflow before real translation.
• Do: add locale rules (date, currency, decimal separators) and test on real devices.
• Don’t: translate brand/product names, URLs, or legal entity names.
• Don’t: publish without hreflang tags and translated meta titles/descriptions if you care about SEO.

What you’ll need

• A spreadsheet (CSV/Google Sheet) with columns: key, English, notes, char limit, placeholders, tone, and one column per language.
• A 15–30 term glossary (must-keep English terms + approved translations).
• One native reviewer per language for spot checks and critical flows.

Step-by-step: the control sheet method

1. Create keys: Give every string a stable key (e.g., checkout.button.pay).
2. Tag constraints: In notes, mark variables ({name}), code, and character limits (e.g., 18 for mobile buttons).
3. Seed glossary: List brand terms and preferred phrasing; add do-not-translate items.
4. AI first pass: Use the prompt below to fill the language columns. Expect 80–95% good drafts depending on language and complexity.
5. Human review gates: 100% for checkout/legal, 20% for support, 10% for product pages. Record fixes in the sheet.
6. UI test: Import into staging, run pseudo-localization (exaggerated lengths), then real translations. Fix truncation.
7. SEO pass: Translate slugs (where appropriate), meta titles/descriptions, and add hreflang. Keep brand names in English.
8. Publish & learn: Soft-launch to a small audience, track conversion and support tickets, then update glossary and re-run for consistency.

Insider tricks that save time

• Memory by spreadsheet: Keep a “Past Translations” tab. When wording repeats, copy the approved translation; this acts like a lightweight translation memory.
• Variant planning: For UI labels with tight limits, ask the AI for a main translation plus a short fallback. Store both.
• Error scoring: Use a simple LQA scale: Critical (5), Major (3), Minor (1). Accept if score ≤3 per 1,000 words.

Worked example: turn a help article + UI strings into French and German (48–72 hours)

1. Inventory: One 800-word help article + 25 UI strings from the support flow.
2. Sheet setup: Columns — key, English, notes, char limit, placeholders, tone, French, German.
3. Glossary: 20 terms (brand names, feature names, “Shipping”, “Order”, “Reset password”).
4. AI pass: Run the prompt below. Output fills both language columns, includes short variants for labels ≤18 chars.
5. Review: Native reviewers check 100% of the 25 UI strings and the article’s intro, steps, and warnings.
6. Import & test: Stage the content, test on mobile and desktop, fix any wrapping or tone issues.
7. Release & measure: Publish, track support search success and ticket deflection for FR/DE for one week.

Copy‑paste AI prompt (site/UI + help article)

Role: You are a professional translator and localizer. Translate the following English strings into [TARGET LANGUAGES]. Rules: 1) Do not translate brand names, URLs, or anything inside {curly_braces}, %placeholders, HTML tags, or code blocks. 2) Respect character limits when provided; if too long, provide a ShortVariant. 3) Use a friendly, clear tone suitable for customer support; default formality: slightly formal. 4) Follow the glossary exactly; if a term is missing, propose one and flag it. 5) Return CSV rows with these columns: key, English, Notes, CharLimit, Placeholders, Tone, [Language1], [Language1_ShortVariant_if_needed], [Language2], [Language2_ShortVariant_if_needed], Flags. 6) Also output a 10–30 item glossary section (term, translation, note). Content (CSV with columns: key, English, Notes, CharLimit, Placeholders, Tone): [paste your control sheet rows here]

Optional prompt: build the glossary first

From the English content below, extract 10–30 key terms that need consistent translation. For each term, provide: English term, definition in English, do-not-translate? (Y/N), preferred translation in [LANGUAGE], part of speech, sample sentence in [LANGUAGE]. Use a clear, consistent tone suitable for customer support. Content: [paste representative pages here]

Common mistakes & easy fixes

• Variables get translated — Fix: wrap variables in {curly_braces}, add a Placeholders column, and instruct AI “never translate items in braces.”
• Overflowing buttons — Fix: set a CharLimit and request a ShortVariant; test on small phones.
• Inconsistent terms — Fix: lock the glossary and re-run affected strings; store approved phrases in your “Past Translations.”
• Flat SEO — Fix: translate slugs and metadata, add hreflang, and keep brand names in English.

What to expect

• Speed: first two languages live in days if content is organized.
• Quality: near-publishable MT for straightforward text; human review lifts tone, clarity, and trust.
• Maintenance: small ongoing cost if you keep the control sheet and glossary up to date.

72-hour action plan

1. Day 1 (AM): Build the control sheet; create keys; add 20 glossary terms.
2. Day 1 (PM): Run the AI prompt for your top 3 pages + UI strings; set char limits.
3. Day 2: Native review for checkout/legal/support; fix, then stage and run pseudo‑localization; adjust UI.
4. Day 3: Publish to 5–10% of traffic; monitor conversion, error flags, and support tickets; update glossary and re-run any weak strings.

Keep it lean: one sheet, a short glossary, quick AI drafts, targeted human checks, then iterate. That’s how you go multilingual fast without sacrificing trust.

[Author]

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