Localization is often treated as a task that begins shortly before a product enters a new market: export the strings, send them to translators, import the finished files, and launch.
By that point, however, many of the decisions that determine localization cost, speed, and quality have already been made.
The way a company creates content, stores it, updates it, and assigns ownership affects how easily that content can be localized. The same is true of product architecture, development workflows, quality processes, and vendor relationships.
Localization therefore does not begin with translation. It begins with planning.
A strong localization strategy helps a company answer five questions:
- What content should we localize?
- When should localization enter the product workflow?
- Which translation method should we use for each type of content?
- What should we manage internally, and what should we outsource?
- How can we build a process that scales as the product grows?
For B2B funnel prioritization and ROI, see B2B localization strategy. The sections below focus on the content and workflow architecture underneath it.
In the Localize the World series, host Linh Nguyen (Localization Program Manager at PayPal) sat down with Stas Kharevich, Head of Localization, Alconost, to walk through what early-stage localization actually looks like in practice—for founders, product managers, content leads, and localization managers building localization into a software product from day one.
The clips throughout this guide cover five decisions from that conversation: when to test free tools, why content planning comes first, what to keep in-house as localization scales, how to match human, MTPE, or automated workflows to each content type, and why hands-on pipeline experience makes vendor conversations sharper.
In this series — deeper dives on three decisions from the same conversation:
- Why product localization starts earlier than you think
- Human vs. machine translation: how to choose the right workflow
- What to keep in-house vs. outsource in localization
Localization starts before the first translation
The right time to think about localization is not a few weeks before an international launch. It is when the product’s content and systems are being designed—ideally alongside internationalization decisions that keep strings externalized, layouts flexible, and locales swappable from the start. For a focused guide on content planning, system design, and the questions to answer before the first string is translated, see why localization starts earlier than you think.
That does not mean every startup needs a sophisticated localization platform on its first day. It means the team should make early decisions with future localization in mind.
When does localization really begin?
Stas Kharevich on when localization actually starts—and why content ownership, storage, structure, and integrations belong in product planning, not in a pre-launch scramble.
Whenever this idea of creating a product, which has some content, springs to your mind, that's about the right time you start thinking about localizing it. Localization is an integral part of the development process—and it all revolves around your content.
Before the first translation, these seven planning questions help set the foundation:
- What types of content will the product contain?
- Who will create and own that content?
- Where will it be stored?
- How frequently will it change?
- Which systems will need to exchange localized content?
- Will the content be easy to extract and reimport?
- Which markets or languages may become priorities later?
These questions are part of content and product planning, not merely translation management.
A company that stores product strings, website copy, support content, and marketing materials across disconnected systems may eventually need a different localization process for each source. Manual transfers multiply, updates are missed, and it becomes difficult to determine which version is current. At Alconost, we often see teams discover that fragmentation only after they have already chosen a TMS or signed with a vendor.
By contrast, a team that understands its content landscape can design cleaner integrations and workflows from the beginning. See also shipping two languages early to stress-test architecture before scale.
The first step in localization strategy is therefore not choosing a vendor or translation technology. It is creating a clear picture of the content.
Build a content inventory
Most products contain several types of content, each serving a different purpose.
Typical categories include:
- Product interface text
- Website pages
- Onboarding flows
- Marketing campaigns
- Help-center articles
- Product documentation
- Customer support content
- Legal or compliance material
- Internal knowledge bases
- Automated notifications and service messages
Treating all of this content in the same way is rarely efficient.
A homepage headline and an internal support article may contain a similar number of words, but they do not carry the same business risk. A poorly translated advertisement may damage a campaign or brand. A slightly imperfect internal document may still be entirely usable.
Without a content inventory, every localization request becomes a fresh negotiation. A useful inventory should document at minimum:
- Content type
- Business purpose
- Audience
- Owner
- Source system
- Update frequency
- Expected volume
- Visibility
- Business risk
- Required quality level
- Target languages
This inventory becomes the foundation for localization prioritization.
Profile content by visibility and business impact
Should we use human or machine translation? That familiar question is too broad. For a full decision framework—including visibility tiers, post-editing levels, language pairs, and a workflow scoring matrix—see human vs. machine translation: how to choose the right workflow.
The better question:
What translation workflow is appropriate for this specific type of content?
Human translation, AI, or both?
On matching workflow to visibility: content volume, purpose, risk, and required quality all influence the decision—not a blanket preference for human or machine translation.
Nowadays it's popular to divide content by visibility—high, medium, or low. High-visibility content influences retention and acquisition, so you need to focus on quality. For low-visibility content with high volume, automated workflows can be absolutely okay when the output quality is designed and monitored.
Content can be divided into high-, medium-, and low-visibility tiers.
| Tier | Examples | Typical workflow |
|---|---|---|
| High visibility | Product UI, homepage, ads, onboarding, app-store copy | Human translation, transcreation, subject-matter review, LQA |
| Medium visibility | Blog posts, secondary pages, educational content, routine marketing | Machine translation + human post-editing (MTPE) |
| Low visibility | Internal docs, large knowledge bases, archived support, rare service messages | Automated translation and automated review where risk is low and output is monitored |
Reader checkpoint: If you only do one thing this quarter, classify your top 10 content types by visibility and assign a workflow to each.
1. High-visibility content
This tier carries reputation and revenue risk. When copy shapes first impressions, conversion, or trust, the appropriate default is human translation, transcreation, or intensive review—including linguistic testing in the actual product. The failure mode is not a typo in isolation; it is a broken onboarding flow, an off-brand campaign, or UI copy that reads like an afterthought.
2. Medium-visibility content
This content is customer-facing but rarely the first thing a user sees. Machine translation with human post-editing (MTPE) often fits here when speed and cost matter and the content is not the primary conversion surface. See also how AI fits into localization workflows for where automation helps and where human review still matters. The level of post-editing can vary: some pieces need publication polish; others only need to be accurate and clear.
3. Low-visibility content
This tier often combines high volume with low individual impact—internal documentation, archived support material, rare service messages. Automated translation plus automated review can work when the workflow has been tested and output quality is monitored. The failure mode is not one bad sentence; it is applying premium human translation to hundreds of thousands of words that almost nobody reads, or conversely, letting raw machine output into a tier that quietly erodes trust when users do find it.
Content profiling allows companies to invest the most effort where quality matters most instead of applying an expensive workflow to every word.
Consider volume, frequency, and lifespan
Visibility is only one part of the decision. Translation workflows should also reflect:
1. Volume
A few thousand words can often be handled efficiently through conventional human translation. Hundreds of thousands require a different operating model—translation memory, automation, machine translation, terminology management, and continuous workflows.
2. Update frequency
Content that changes once a year can be managed differently from content released every day.
Frequently updated products benefit from integrations that automatically detect, send, and retrieve new strings. Manual exports may be manageable at first but become a bottleneck as release frequency increases.
3. Content lifespan
A major brand page may remain visible for years and justify significant editorial investment.
A temporary support notice or short-lived campaign variation may not.
4. Repetition
Products often contain recurring phrases, interface patterns, and documentation fragments. Translation memory can reuse approved translations, reduce cost, and improve consistency.
5. Risk
Legal, medical, financial, security-related, or safety-critical content may require specialist translators and additional review regardless of its visibility or volume.
The objective is not to minimize human involvement at all costs. It is to assign the right level of human and technological involvement to each content category.
Decide what to own internally
A company does not necessarily need a large internal translation department to build a strong localization program. For a detailed breakdown of strategic ownership vs. production execution—and what to keep in-house when scaling across languages—see what to keep in-house vs. outsource in localization.
Many organizations outsource most translation production. What they should not outsource entirely is ownership of the localization strategy.
The internal team should usually retain responsibility for:
- Localization goals
- Market and language priorities
- Content ownership
- Quality expectations
- Product and brand terminology
- Style requirements
- Workflow governance
- Technology decisions
- Vendor management
- Success metrics
- Final product-level quality
An internal localization manager can connect product, engineering, marketing, content, support, and external vendors. This person does not need to personally perform every task. Their role is to ensure that all the parts of the process work together.
Some companies may also keep product or linguistic quality assurance in-house. Internal reviewers often understand the product context, customer expectations, and release priorities better than an external production team.
What should your internal team actually own?
A company can outsource most translation production without giving up control of its localization program. In the clip below, Stas Kharevich on workflow ownership, requirements, content management, and final quality oversight.
What I would keep in-house is the localization managers in charge of the pipeline and workflow—the rules and requirements sent to vendors, content generation and content management, and maybe a small team of QA managers for the last phase before release. Task management, translators, and routine internal QA are often best outsourced.
Decide what to outsource
Execution-heavy activities are often easier to scale through a localization partner.
These can include:
- Recruiting and managing translators
- Assigning translation tasks
- Maintaining language teams
- Translation and editing
- Linguistic quality control
- Desktop publishing
- Multimedia localization
- Engineering support
- Machine translation setup
- Routine workflow administration
A vendor can provide capacity across languages without requiring the company to recruit and coordinate every specialist directly. Read more in our guide to outsourcing localization.
The key distinction is between strategic ownership and production execution.
A company may outsource nearly all translation work while still maintaining strong control over:
- What gets localized
- When it gets localized
- Which workflow is used
- What quality means
- How results are evaluated
Outsourcing works best when the client can provide clear requirements, reliable source content, product context, terminology, and feedback.
Build localization maturity
Hiring a vendor does not remove the need for internal localization knowledge.
A company with localization maturity understands its own pipeline well enough to make informed decisions and diagnose problems.
Why does localization maturity matter—even when you outsource?
Stas Kharevich on why internal pipeline knowledge still matters when a provider handles production.
Localization maturity is the knowledge and experience you gain to build your own localization pipeline—you know how your CMS integrates with your TMS, what stages your workflow has, and where to go when something breaks. That helps you decide exactly what to outsource and what to keep.
A localization-mature company knows:
- Where source content comes from
- How content enters the localization workflow
- Which steps are automated
- Which steps require people
- How translations are reviewed
- How localized content returns to the product
- Who is responsible when something breaks
- Which content requires which quality level
- Which metrics indicate whether the process is working
Localization maturity develops gradually. The staged model below is a synthesis of patterns we see across client programs—not a formal industry standard.
Stage 1: Reactive localization
Localization begins late, often shortly before launch. Content is transferred manually, responsibilities are unclear, and each project is treated as a one-off request.
Stage 2: Repeatable localization
The company establishes basic processes, recurring vendors, terminology resources, and ownership. Projects still require manual coordination, but the workflow is more predictable.
Stage 3: Integrated localization
Content systems, repositories, and localization platforms are connected. New content can move through the workflow with less manual handling. Localization becomes part of product and content operations.
Stage 4: Optimized localization
The company profiles its content, applies different workflows by business value, measures quality, and improves automation. Human translation, machine translation, and post-editing are chosen by content risk, not team preference.
Stage 5: Strategic localization
Localization data contributes to product and market decisions. The company evaluates performance by language and market, adapts content strategies, and treats localization as part of international growth rather than an isolated service. Track outcomes with a localization ROI framework as maturity increases.
Not every organization needs to reach the highest level immediately. The relevant question is whether its localization capabilities match the complexity of its product and international operations.
Start small and learn from a pilot
Startups often have limited budgets and small teams—and may not be ready for enterprise localization infrastructure. They often have something else: time to research, test free tiers, and learn how a workflow behaves in their stack before committing to a large investment.
Many localization platforms and related tools offer free plans, trials, or entry-level options worth testing before signing an annual contract.
How can startups begin with limited resources?
Stas Kharevich on experimenting with free plans and entry-level tools before larger investments.
Most startups are limited on people and budget—but they often have time to research. There are plenty of tools with free starting plans. Test them yourself against your infrastructure so you understand the basics of the localization pipeline you are going to build.
A small pilot can help a team understand:
- How content is imported
- Which file formats are supported
- How translators work in the platform
- How terminology is managed
- Whether the tool integrates with the existing stack
- Which manual steps remain
- How translated content is exported
- Which limitations appear as volume grows
The purpose of the pilot is not merely to select software. It is to learn how the company’s localization pipeline should work. We often see teams skip this step and discover integration gaps only after they have already committed to a platform or vendor contract.
A simple pilot might include:
- Select one language.
- Choose a small but representative content set.
- Define the required quality level.
- Test one or two translation workflows.
- Import the content into a localization platform.
- Review the output in context.
- Document problems and manual steps.
- Estimate what would happen at ten times the volume.
This process gives the company better information before it commits to tools, hires, integrations, or vendors.
Create a minimum viable localization workflow
An early-stage localization process does not need to be complex.
A minimum viable workflow may look like this:
- Content is created in a defined source system.
- The content owner marks it as ready for localization.
- Content is sent to a localization platform or provider.
- The appropriate workflow is selected based on content type.
- Translation and review are completed.
- The content is returned to the source system.
- The localized product or page is tested in context.
- Feedback is recorded for future releases.
Even at this stage, the team should establish several basic resources.
Glossary
A glossary contains approved translations of product names, features, technical terms, and recurring concepts.
Style guide
A localization style guide defines tone, audience, formality, capitalization, punctuation, formatting, and language-specific preferences. For high-visibility copy, also plan for cultural and register pitfalls that translation alone cannot fix.
Clear ownership
Every content type should have an owner who can answer questions and approve important decisions.
Feedback process
Translators and reviewers need a consistent way to raise questions and receive context. Internal teams also need a way to report localization issues without losing them in unrelated product tickets.
Basic metrics
Useful early metrics may include:
- Turnaround time
- Cost per content type or language
- Number of corrections
- Rework rate
- On-time delivery
- Percentage of reused translations
- Localization-related release delays
The goal is not to create a large reporting system. It is to understand whether the process is becoming more reliable.
Avoid the most common localization mistakes
These patterns make localization more expensive than it needs to be:
1. Starting too late
When localization begins after the product and content architecture are fixed, teams often discover hard-coded strings, unsuitable layouts, unsupported formats, and fragmented content sources—sometimes mid-launch, when fixes are slowest.
2. Localizing everything with the same workflow
Not every word requires the same quality level. Applying premium human translation to low-risk, high-volume content can waste budget, while applying raw machine translation to high-impact marketing content can create reputational risk.
3. Outsourcing responsibility along with production
A vendor can manage translation, but the company still needs internal owners who define priorities, requirements, and quality.
4. Choosing tools before understanding the workflow
A platform may have an impressive feature list but still fit poorly with the company’s content systems and release process.
5. Ignoring context
Translators need to know where text appears, who will see it, what action it supports, and whether there are character or design constraints.
6. Measuring only cost per word
A low translation rate does not necessarily produce a low total cost. Manual coordination, engineering work, rework, delayed launches, and inconsistent terminology can be much more expensive. See our localization cost guide for what actually drives total spend.
A practical localization roadmap
Companies beginning or redesigning their localization program can use the following sequence.
Step 1: Map the content
Document content types, owners, systems, volume, update frequency, and business importance.
Step 2: Prioritize markets and languages
Base decisions on product strategy, customer demand, market potential, support readiness, and operational capacity. For SaaS products, SaaS localization has its own sequencing and content priorities. For B2B products, see also where to invest first in the funnel.
Step 3: Profile content
Group content by visibility, risk, lifespan, and required quality.
Step 4: Assign workflows
Choose human translation, machine translation with post-editing, automated translation, or a specialized workflow for each category.
Step 5: Define internal ownership
Appoint someone responsible for localization decisions, cross-functional coordination, and vendor management.
Step 6: Run a pilot
Test a small but realistic localization cycle using actual content and product systems.
Step 7: Establish terminology and style
Create the minimum resources translators need to produce consistent work.
Step 8: Add integrations where they remove real bottlenecks
Automate the most repetitive transfers first rather than trying to automate the entire process immediately.
Step 9: Evaluate quality in context
Review localized content in the website, application, game, or product environment—not only in a translation file.
Step 10: Improve the process as the company grows
Revisit content tiers, workflows, technology, vendors, and metrics as volume and language coverage increase.
Localization is an operating capability
A scalable localization program is not built by choosing between humans and machines, buying a particular platform, or sending content to a vendor.
It is built by understanding your content, matching workflows to business needs, maintaining internal ownership, and improving the pipeline over time.
For a startup, that may begin with a spreadsheet, a free tool, one language, and a small pilot. For a mature organization, it may involve integrated systems, multiple vendors, automated workflows, and content-specific quality models.
Use the right process for the right content, and build enough internal knowledge to understand and control the result.
When you design localization this way, it becomes more than a step at the end of production. It becomes part of how you build products for international users.
Stas Kharevich has spent more than 16 years at Alconost and leads localization for product and software teams—SaaS, games, and marketing content among them. The video clips in this guide are from his conversation with Linh Nguyen on the Localize the World series. Read more from Stas on how Alconost runs localization.
