You’ve googled “how much does software localization cost” and every result either wants to sell you a platform or tells you “it depends.”
It does depend. But it’s not a mystery. The pricing follows a structure, and once you see it, you can estimate a budget, build a plan, and explain the whole thing to whoever needs to sign off on the spend.
I’m going to walk you through the same breakdown I share on every first call with a new client. This is how I explain it when a PM or an engineer sits down with me and says “we need to localize our product, what are we looking at?”
How Software Localization Cost Breaks Down
Software localization costs fall into two buckets. Once you understand these, everything else is just detail.
Per-Word Pricing for Translation
Everything where a linguist works with a text file gets priced per word. UI strings, help center articles, documentation, email templates, onboarding copy, error messages. These are all part of our service offering. We see the source file, we quote a per-word rate for each target language.
Rates vary by language pair, and the factors aren’t always obvious. The level of human involvement versus AI, creativity requirements, language combination, and the outcome you need all play a role. A straightforward UI string file going through AI with human review costs less per word than a marketing page that needs a native copywriter working from scratch. Rather than guessing, it’s worth getting an actual quote for your specific language list early on.
Per-Hour Pricing for QA and Review
Anything where a specialist needs to interact with the live product rather than just review a text file gets priced per hour. In-context testing in staging environments, visual QA for truncation and layout issues, voice output review for conversational AI, deep terminology audits across screens. Hourly rates for this type of work typically sit between 40 and 80 USD, depending on the language and depth of review.
Most projects involve both. You translate the content (per word) and then verify it works inside your product (per hour). Some teams only need the translation. Others want the full check, especially when a truncated button or awkward phrasing registers as a product issue to their users. Because that’s what it is. Users don’t think “bad translation.” They think “this app feels broken.”
- UI strings and in-app copy
- Help center and support articles
- Developer documentation
- Email templates
- Marketing and landing pages
- Voice and conversational scripts
- In-context review in staging
- Visual QA for UI truncation
- Voice output testing (TTS/STT)
- User flow walkthroughs
- Terminology consistency checks
- Bug reporting and adjustments
Translation memory saves money over time. Every translated segment gets stored. Repeated content across updates and features gets matched automatically. You only pay full rate for new or changed content.
What Affects Software Localization Cost
The price tag depends on decisions you make about what gets localized, how it gets translated, and how thoroughly it gets checked. Here’s where most of the variance comes from.
Content Types and Translation Approach
Not every piece of content in your product costs the same to localize, and this is where the conversation usually starts on a first call. I ask: what do you have, where does it live, and what format is it in?
UI strings and structured content like JSON, XML, or .strings files are the most straightforward to localize. They’re short, repetitive, and technical. AI handles the first draft, and a native speaker reviews and tightens it. This is faster, costs less per word, and you still get professional human oversight on every string.
Help center articles and documentation fall into a similar range. Lots of repeated terminology, structured formatting, content that needs to be clear and consistent more than it needs to be compelling.
Marketing pages, onboarding flows, and anything where tone and persuasion drive conversion are different. A landing page that converts in English won’t convert in German just because the words are technically correct. The argument, the emphasis, sometimes the entire structure needs to shift. That’s human-heavy creative rather than translation, and costs are calculated by hours spent because the work is fundamentally different.
This content mapping is probably the most important part of the first conversation. It determines the approach for each content type, and the approach determines the software localization cost.
.json .xml .strings .arbButtons, menus, labels, error messages. Structured and repetitive. AI drafts well, humans catch context and truncation.
.md .html CMSSupport docs, FAQs, knowledge base. Consistent terminology matters more than creative flair.
.md .rst .yamlAPI docs, integration guides. The audience demands accuracy more than polish.
.json CMS in-appFirst impressions. Tooltips, welcome screens, guided tours. Tone directly affects activation.
.html CMS WebflowLanding pages, feature pages, pricing. These need to convert, not just communicate.
.html ESP .jsonTransactional emails, notifications, campaigns. Templated structure, AI handles the base.
Translation Memory and Reuse
Every translation we produce gets stored in a database of previously translated segments. If your help center articles share common phrasing, or your product has repeated patterns across features, you don’t pay again for content that’s already been translated. Only new or changed segments get billed at full rate.
For products with regular update cycles, translation memory can cut ongoing costs by 30 to 50 percent compared to the initial project. The more content you push through the system, the more the database grows, and the cheaper each subsequent round becomes. It’s one of the reasons localization gets more cost-effective over time rather than staying flat.
QA Depth
This is the lever most people don’t think about until it shows up in a quote.
A basic review that confirms translation accuracy and natural phrasing costs less than having specialists walk through every user flow in staging, checking for truncation, layout breaks, date and number formatting, and cross-screen terminology consistency. The deeper you go, the more hours it takes, and the more it costs.
Most teams don’t need the same depth everywhere. A settings menu might be fine with standard review. Your checkout flow or onboarding sequence probably warrants a closer look. We usually recommend starting with standard review across the board and adding depth where it matters most. You can always go deeper on the next round once you see where the problems cluster.
Software Localization Cost for SaaS Products
SaaS products have a few cost dynamics that are worth understanding upfront, because they’re different from localizing a document or a one-time marketing campaign.
Starting Small vs. Full Rollout
You don’t need 30 languages on day one. A company came to us recently with an enterprise client who needed their product available across 28 markets. They already had a plan to roll it out over a year to 18 months, which is exactly the right instinct.
Starting with a handful of priority markets lets you prove the workflow, build terminology, and iron out the process before you scale. Each additional language gets its own translation memory and glossary built fresh, but the workflow, the quality benchmarks, and the approach are already proven. It’s the same phased logic that helped Netflix reach 190 countries over 7 years — start close to home, learn, then accelerate. Expanding from 5 to 15 languages is nothing like going from 0 to 5.
Ongoing Cost vs. Initial Investment
The first batches of software localization cost the most. You’re translating everything from scratch, building the glossary, setting up the workflow, working through the first round of QA. After that, costs drop significantly because you’re only paying for new and changed content each cycle.
Vault came to us after running AI translations across their platform without human review. The translations were live in multiple languages, but their team couldn’t tell whether the output was actually good. They couldn’t read the languages. They couldn’t check if terminology was consistent between screens. They couldn’t assess tone.
That’s a pattern I see a lot. A team uses AI to translate everything, and on the surface it looks done. But nobody can validate what shipped. The cost of “free” AI translation is uncertainty. And when that uncertainty surfaces (usually because a client or a user flags something embarrassing), the cleanup costs more than doing it right the first time would have.
The smarter approach is using AI where it works well, structured content with repetitive terminology, and putting human review where it matters. That’s how we scaled Reputation’s global efforts without blowing up their timeline. That’s roughly 60 to 70 percent AI-assisted and 30 to 40 percent human-first for a typical SaaS product. You get speed and cost savings without the blind spot.
McKinsey’s research on corporate growth patterns found that half of all growth in the decade to 2019 came from international markets. The companies that got the most out of that expansion were the ones that could beat local competitors on their own turf — and that starts with the product feeling native.
How to Present a Localization Budget Internally
If you’re the person who needs to take software localization costs and plan to your VP, CTO, or the enterprise client who asked for multilingual support, here’s what they’ll want to know. I’ve structured this so you can screenshot it or drop it into a Slack thread.
How much will this cost? Translation is per word, QA is per hour. For a typical SaaS product launching in 5 languages with standard review, initial cost depends on content volume but follows predictable per-word rates. Ongoing costs drop as translation memory grows, because you only pay for new and changed content each cycle.
How long until we see results? First delivery within 1 to 2 weeks of receiving source files for a focused scope. After that, localization runs alongside your releases. Updates under 500 words turn around in 24 to 48 hours.
What’s the quality guarantee? Native speakers review every output. QA depth is adjustable, from accuracy checks to full in-context testing in staging. Certified under ISO 17100, the international standard for translation services, and ISO 9001. Human accountability on every deliverable.
What does our team need to do? Share source files, confirm target languages, give access to staging for QA. Engineering doesn’t adopt new tools or change how they release.
Can we start small and scale later? Yes. Start with 3 to 5 priority languages, prove the workflow, then expand. Each new language gets its own translation memory and glossary, but your processes and quality benchmarks are already in place. And the more content you run through the system, the more gets recycled, which is where costs come down over time.
Workflow Integration and Timeline
One thing that surprises most teams: the integration doesn’t have to be expensive or complicated. If your strings live in GitHub or GitLab, we connect there. If you use Crowdin or Phrase or any other TMS, we work inside it. Jira? Localization gets a lane in your existing board.
On your side, the lift is minimal. Share source files, confirm target languages, give us staging access for QA. Your engineering team doesn’t need to adopt new tools or restructure anything.
How Long Does Software Localization Take
The typical sequence looks like this. First call covers scoping and approach, usually 45 minutes or so. We follow up with a detailed quote within a day. Once source files arrive, the first delivery lands within 1 to 2 weeks, depending on scope and QA depth. After that initial batch, localization becomes continuous. New features, updated strings, fresh documentation. Everything flows through the same pipeline, aligned with your release cadence.
Worth saying clearly: this isn’t a project with a finish line. It’s an ongoing operation that runs alongside your product development. And it gets cheaper over time as translation memory builds up and terminology stabilizes.
Scoping CallDay 1Map content, file formats, languages, priorities. |
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Quote and KickoffDay 2–3Per-word rates, QA hours, delivery timeline. Specialist teams onboarded. |
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Translation + First QAWeek 1–2Content translated, first QA round, initial outputs shared for review. |
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First DeliveryWeek 2–3Final files in your formats. Translation memories stored. Ready to deploy. |
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Continuous OperationOngoingSmall updates in 24–48h. Larger batches match your sprints. Costs drop over time. |
Let’s Talk Numbers
If you’re putting software localization costs together, or you’re trying to figure out whether your current setup is giving you good value, I’d love to walk through the specifics for your product. No pitch deck. Just a conversation about your content, your languages, and what the numbers actually look like.
FAQ
Translation is priced per word, QA is priced per hour (40–80 USD). For a typical SaaS product launching in 5 languages with standard review, initial cost depends on content volume but follows predictable per-word rates. Ongoing costs drop as translation memory grows, because you only pay for new and changed content each cycle.
First delivery within 1 to 3 weeks of receiving source files, depending on number of languages and QA depth. After that, localization runs alongside your releases. Updates under 500 words turn around in 24 to 48 hours.
Native speakers review every output. QA depth is adjustable, from accuracy checks to full in-context testing in staging. ISO 9001 and ISO 17100 certified processes. Human accountability on every deliverable.
Share source files, confirm target languages, and give staging access for QA. No new tools to adopt. The localization partner integrates with your existing workflow: GitHub, Jira, Slack, or whatever your team already uses.
Yes. Start with 3 to 5 priority languages, prove the workflow, then expand. Each new language gets its own translation memory and glossary, but your processes and quality benchmarks are already in place. Costs come down over time as more content gets recycled.
