The question every business leader faces when going global isn't whether to localize — it's where to invest first. With finite budgets and dozens of possible touchpoints across the marketing and sales funnel, the real cost isn't what you spend on localization. It's the revenue you leave on the table by localizing the wrong things — or nothing at all.
In a recent conversation on The Agile Brand Podcast, Ilya Spiridonov, Alconost's Chief Commercial Officer, shared the strategic framework he uses when advising enterprise and SaaS clients on localization strategy. The insights below are drawn directly from that conversation.
Where Companies Misallocate Their Localization Budget
One of the most expensive mistakes in B2B localization isn't choosing the wrong language — it's trying to do everything at once. Companies treat market entry as a binary switch: either we're fully localized or we're not. That all-or-nothing mindset burns budgets fast and delays the learning you need to localize effectively.
One of the biggest misallocations is probably assuming that going to market requires localizing everything at once, right away. In reality, early-stage localization should look like experimentation more than a full-scale rollout. It has to follow the go-to-market strategy, but otherwise it has to be more agile — more step by step.
This experimental approach doesn't mean cutting corners. It means being intentional about what you localize first, measuring the results, and expanding based on data. A landing page in German that converts tells you far more about market potential than a fully translated knowledge base that nobody reads.
The cost of localization is always relative to what it unlocks. A company spending $50,000 to localize their entire help center into five languages before validating product-market fit in any of those regions has fundamentally misallocated their budget — regardless of how good the translations are.
Signals That It's Time to Localize
So how do you know when to pull the trigger on a new market? Ilya describes two levels of signals that leaders should watch for — one strategic, one operational.
Strategic signals: competitive landscape
The first set of signals comes from looking at your competitive environment. If your competitors are already localizing into certain markets, they're capturing demand you're invisible to.
Is your competition doing that already? If you have three competitors, one is localizing, the other two are not — if you start localizing, you only really have one competitor.
This competitive lens is especially powerful in B2B markets where the number of viable vendors is small. Localizing can immediately cut your competitive set in half in a given region.
Ground-level signals: your own data
The second set of signals lives in your analytics. Traffic from non-English-speaking regions on English-only pages. Sharp drop-offs in signup completion from specific geographies. Demo-to-close rates that underperform in certain regions. For e-commerce, it's checkout completion and abandoned carts. For SaaS, trial-to-paid conversion ratios.
Compare these metrics across regions. When you see irregularities, ask: is localization likely to improve this, or is there another problem? That hypothesis-driven approach prevents you from localizing as a reflex and instead ties every localization decision to a business outcome.
B2B is often B2B2C
One of the more nuanced points Ilya raises is about who actually uses your product — which isn't always your buyer.
B2B businesses assume that localization is not always for them because they sell to corporate. In reality, many B2B businesses are B2B-to-C from a localization perspective. Take a CRM product — it's a B2B business, but the users are the C. If the users are multilingual, they need to consume the content in other languages.
This reframing matters because it shifts the localization priority from sales materials (which the buyer reads) to the product UI and support content (which the end users interact with daily). Your enterprise buyer might be comfortable in English, but their team of 200 users in Germany might not be. Understanding this distinction is critical for getting localization right.
How to Prioritize Touchpoints Across the Funnel
Once you've decided which markets to enter, the next question is what to localize first. Not all content carries the same weight, and not all content requires the same quality bar.
The framework is straightforward: match the workflow to the risk.
High-visibility, high-risk content — marketing landing pages, product UI, legal and compliance materials — needs human translation, often with additional linguistic QA on a staging environment. One bad sentence in a contract or a clumsy phrase on your homepage can be expensive.
High-volume, lower-risk content — SEO articles, help documentation, knowledge base articles — can use AI translation with human post-editing (MTPE). The speed and cost benefits are significant, and the risk of a quality issue causing business damage is lower.
Internal and transient content — internal communications, rapidly changing content — may work with pure AI translation, depending on your risk appetite.
The key is having a clear map of your content types, who sees them, and what happens if the quality isn't perfect. That map becomes the foundation of your localization strategy and determines how you allocate budget across the funnel.
AI vs Human Translation: Beyond the Cost Debate
The AI vs. human translation conversation is one of the most common — and most oversimplified — discussions in localization today. Ilya reframes it around what actually matters for business decision-makers.
It's not only cost and quality — it's also speed. Suddenly it becomes a multivariate problem. But in the end it boils down to risk and risk appetite. Choosing between AI or human or a mix of the two is usually about matching the workflow to the risk.
The right answer is almost never "all AI" or "all human." It's a hybrid approach where different content types flow through different workflows:
UI strings: Human translation first, followed by linguistic QA on the actual localized build (staging server). This catches context-dependent issues that translators can't see in a spreadsheet.
SEO content: AI translation with optional human post-editing. High volume, lower stakes, speed matters.
Legal and compliance: Human only. The cost of an error far outweighs any savings from automation.
Marketing and brand content: Human translation with transcreation where needed. Brand voice doesn't survive automated translation.
The challenge for most organizations isn't choosing a workflow — it's having the infrastructure to run multiple workflows simultaneously. That requires centralization, which brings us to the operational side of localization strategy.
Designing for Continuous Localization from Day One
The most expensive localization decision many product teams make is one they don't realize they're making: deciding to think about localization later.
The biggest risk is not designing for continuous localization in the first place. Product teams will say, 'We're going to build this beautiful product and then at some point we're going to localize it.' It doesn't work this way. You need to design for continuous localization — incremental updates instead of massive batches.
Continuous localization means several things in practice:
Internationalized codebase: Your product needs to support multilingual content from the start — externalized strings, ICU message format for plurals and numbers, support for RTL languages if relevant.
CI/CD integration: New strings should flow into a translation management system (TMS) automatically as part of your build pipeline, and translations should flow back just as seamlessly.
Staging environment for localized builds: Translators and QA reviewers need to see strings in context, not in isolation. This requires CTO buy-in because it affects development culture.
Centralized localization ownership: When multiple teams produce content — product, marketing, support, legal — someone needs to own consistency. Terminology, brand voice, and workflow standards can't be maintained in silos.
The expertise required to run hybrid AI-human workflows efficiently is substantial. As Ilya notes, the shift toward AI-based workflows across the industry has created a new challenge: companies cutting costs with AI without having the expertise to manage the quality risks that come with it. That expertise needs to be either nurtured internally or brought in through an experienced localization vendor.
Measuring Localization ROI
Measuring localization ROI is one of the most-asked questions in the field — and one of the hardest to answer cleanly. The direct approach is straightforward: compare revenue from a localized market against the cost of localization for that language.
But Ilya is honest about the limits of direct measurement. Much of localization's value operates the same way brand awareness does — you know it matters, but you can't always draw a straight line from spend to revenue.
The practical approach is to track regional metrics before and after localization:
Conversion metrics by region: Signup completion, trial-to-paid, demo-to-close rates
Revenue per localized language: Direct attribution where possible
Engagement signals: Time on site, bounce rate, support ticket volume from localized regions
Competitive positioning: Are you winning deals in localized markets you previously lost?
But beyond the spreadsheet, there's a strategic reality that numbers alone don't capture: localization is fundamentally about competition. In many markets, the choice isn't between localizing and saving money — it's between localizing and being invisible.
As Ilya puts it: "Sometimes localization, even though it's not directly measurable, is still crucial because it gives you competitive edge. Localization in most cases is about competition — competition globally."
Frequently Asked Questions
What is the first step in building a B2B localization strategy?
Should B2B companies use AI or human translation?
How do you measure the ROI of localization?
Why is continuous localization important for B2B products?
Ilya has spent 10+ years helping companies scale globally through localization. As CCO at Alconost, he works directly with enterprise and SaaS clients on localization strategy, vendor selection, and ROI optimization. Connect on LinkedIn.
