The Easiest Business Case in Localization
Most localization investments are justified with revenue arguments that require assumptions: more reach, better engagement, eventual conversion.
Support content has a simpler case. A customer who resolves their own problem does not contact support. A contact avoided has a known cost — the fully loaded cost of handling it. Localized support content that measurably reduces contacts in a market has produced a measurable saving.
This makes support video one of the few localization categories where the return can be calculated rather than argued, and where the calculation frequently favours localization strongly in markets where support is being delivered in a language the customer does not speak comfortably.
There is a secondary benefit that matters as much: customers who cannot self-serve in their own language contact support in a language they struggle with, which lengthens handling time, increases misunderstanding, and produces worse outcomes. Localized self-serve content improves the experience of the contacts that do happen by removing the ones that should not have been necessary.
Prioritize by Ticket Volume
The ranking signal for support content localization is not view count or content quality. It is ticket volume by topic and by market language.
Pull the data: which topics generate the most contacts, broken down by the customer's language. This immediately reveals where localized content would deflect most.
Several patterns commonly appear:
High-volume topics in markets with no localized content are the obvious priority and usually the largest single opportunity.
Topics with high volume in one language and low volume in another, where the difference is not explained by market size, often indicate that existing content in the second language is working — which is useful validation.
Topics with high volume everywhere point at a product problem rather than a content problem. Localizing content about a confusing feature helps; fixing the feature helps more.
Contacts in the dominant language from customers whose profile language is different indicate customers falling back to a second language because nothing exists in their first. These are strong localization candidates and are frequently invisible in language-tagged reporting.
Rank by volume multiplied by expected deflection rate. Some topics deflect well with good content — procedural questions, setup, common errors — while others do not, because the customer needs account-specific action that no article can provide.
Terminology Must Match the Product
Support content shares the product video constraint: terminology must match what the customer sees in their localized interface.
A support video telling a customer to click something that is labelled differently in their language is worse than no video, because the customer follows the instruction, cannot find the element, and contacts support anyway — now frustrated.
Derive the terminology from the product's localized string files rather than translating independently. Where the product ships an interface in a language, that interface defines the vocabulary.
Where a feature has not been localized in the product, use the untranslated name, matching what the customer will actually see.
Where the product's own localization is inconsistent — which is common — the support content will surface it. Fix it in the product where possible; where not, match the inconsistency rather than silently correcting it, since matching what the customer sees is what makes the content usable.
Error messages deserve specific attention. A customer searching for help with an error will search using the error text as it appeared to them, in their language. Support content that quotes the source-language error text will not match that search and will not be found.
Content Types and Their Value
Support content spans formats with different localization returns.
Procedural walkthroughs — how to accomplish a specific task — deflect well and localize straightforwardly. These are usually the highest-return category.
Troubleshooting content — diagnosing and resolving a problem — deflects well where the problem is common and the resolution is deterministic.
Setup and onboarding content prevents contacts rather than deflecting them, and its value shows up in activation metrics as well as in ticket volume.
Feature explanation deflects fewer contacts but reduces underuse, which affects retention.
Policy and account content — billing, subscription changes, data handling — generates high contact volume and localizes well, though it may carry regulatory requirements in some markets.
Video versus written content is worth considering per topic. Video excels where the customer needs to see an interface or a physical action; written content is faster to consume and easier to search for simple factual answers. Localizing the right format matters as much as localizing at all, and some topics are better served by translated written content than by translated video.
Findability
Support content that exists but is not found deflects nothing, and findability is where localized help centres most commonly fail.
Search in the customer's language must work, which requires the content, the metadata, and the search index to be in that language. A help centre that stores localized content but searches only source-language metadata will not surface it.
Error text and symptom language should appear in the content, since customers search using the words they see and the words they would use to describe the problem, not the formal feature names.
In-product help links should route to the localized version based on the customer's interface language rather than to the source version.
Support agents should be able to send localized links. Agents handling a contact frequently share help content, and the tooling should surface the version matching the customer's language automatically.
Search terms differ by market in the same way they do for general content. Customers describe problems using vocabulary that may not be a translation of the source-language description.
Instrument search. Failed searches in each language are a direct list of content that should exist and does not, and it is the most actionable input available for prioritizing what to localize next.
Measuring Deflection
The measurement approach that produces a defensible number:
Establish baseline contact volume by topic and language over a stable period.
Publish localized content for a subset of topics.
Measure contact volume for those topics in that language over a comparable period, against both the baseline and a control set of topics that were not localized.
The control matters because contact volume moves for many reasons — product changes, seasonal patterns, customer growth — and comparing only against a prior period attributes all of that movement to the localization.
Normalize for customer growth. Absolute contact volume rises as the customer base grows; contacts per customer is the meaningful measure.
Secondary metrics worth tracking:
Handling time for contacts that do occur, which should fall if customers arrive better informed.
Resolution rate on first contact, which improves when customers can be pointed to content they can read.
Content engagement — views, completion, and helpfulness ratings by language — which indicates whether the content is being found and used.
Escalation rate, which may fall where customers self-resolve simpler issues.
Express the result in cost terms. Contacts avoided multiplied by cost per contact is the number that justifies continued investment, and it is usually large enough to make the case comfortably.
Maintaining a Localized Help Centre
Support content ages faster than most content because it describes a product that changes.
The maintenance obligation scales with the number of languages, and a help centre that accumulates localized content without a maintenance process degrades into a library of increasingly wrong instructions.
Practices that make this manageable:
Tag content by product area so that release changes can be cross-referenced against affected content across all languages.
Version content against the product, recording which release each localized version reflects.
Prefer concept over click path where possible, since content describing what to accomplish outlasts content describing exactly where to click.
Batch updates at release boundaries rather than continuously, so that a coherent set of changes propagates together.
Retire aggressively. Content about removed features should be withdrawn in every language simultaneously. Orphaned localized content describing functionality that no longer exists generates contacts rather than deflecting them.
Segment scripts and archive them so that a changed step can be regenerated without reproducing the whole video.
Agent-Facing Content
An often-overlooked category: content for support agents rather than for customers.
Agents supporting customers in multiple languages benefit from internal documentation and training in their own language, particularly where the agent workforce is distributed.
This content has different requirements — it can assume product knowledge, uses internal terminology, and is not customer-facing — but it affects customer outcomes directly through handling quality.
It also has a specific terminology requirement: agents need to know both the internal terminology and the customer-facing terminology in each language they support, and content that conflates them causes agents to use internal names with customers.
Coordinating With the Support Organization
Support content localization touches the support organization directly, and coordination determines whether it lands.
Agents should know what exists. Content localized without informing the agents who could point customers to it deflects far less than it could. A short internal notice per release, in the languages the agents work in, closes this gap cheaply.
Agent feedback is the best content signal available. Agents know which explanations work, which questions recur, and where existing content fails. Routing their observations into the localization backlog produces better prioritization than ticket-topic data alone, because agents know why a topic generates contacts.
Macro and canned response localization should align with the video content. Where an agent's standard response links to a help article, the localized response should link to the localized article, and the terminology in both should match.
Escalation paths should account for language. A customer who watched localized content and still needs help should reach someone who can assist them in that language. Localized self-serve content that funnels into source-language-only support produces a worse experience than no localization, because it raises an expectation the organization cannot meet.
Measure jointly. Deflection is a support metric, and the localization programme should report against it alongside the support organization rather than in a separate content report. Shared measurement keeps both parties working toward the same result.
Getting Started
Pull ticket volume by topic and by customer language, and rank by volume multiplied by expected deflection.
Derive terminology from the product's localized strings, including error message text.
Localize the top topics in the highest-volume underserved language first, rather than spreading across many languages.
Verify findability: search in the target language, in-product help routing, and agent tooling.
Instrument failed searches per language as the input to the next round of prioritization.
Measure deflection against a control set, normalized for customer growth, and express the result in cost.
Establish the maintenance process — tagging, versioning, retirement — before the library grows large enough to make it unmanageable.
Expect the ranking to shift as you work. Deflecting the top topics changes the distribution, and the topics that were second-tier become the largest remaining opportunity. Re-pull the ticket data before each round rather than working through a list assembled once, since the list is a snapshot of a distribution the work itself is changing.
Support localization is unusual in that its value is defensive rather than aspirational: it does not create new demand, it removes friction and cost from demand that already exists. That makes it less exciting than market expansion and considerably easier to justify, and it is frequently the localization work with the shortest payback period available.
Written Content Versus Video
Not every support topic is best served by video, and localizing the wrong format wastes effort.
Video excels where the customer needs to see something: an interface path, a physical action, a spatial relationship, or a result they need to recognize. Demonstration is what video does that text cannot.
Written content excels where the customer needs a specific fact, a value to enter, a policy answer, or a step they can follow at their own pace while doing something else. It is faster to consume, easier to search within, and easier to update.
Written content is also substantially cheaper to localize and maintain, which matters across many languages and a large topic set.
A reasonable division: localize written content broadly across topics and languages, and localize video selectively for the topics where demonstration genuinely helps. This delivers more coverage per unit of budget than localizing video uniformly.
Where both exist for a topic, they must agree. A customer who reads one thing and watches another that contradicts it contacts support, which is the outcome the content was meant to prevent.
