Demand researched in the language people actually search, claims tied to evidence that holds in that market, and no page live until a native reviewer has signed it off.

A translated keyword list rarely captures the language, questions, and product expectations behind a local search journey, and it can carry claims into a market where the offer or the evidence behind it doesn't apply. We research demand in the language people actually search, map where local intent and terminology diverge from the source market, and build native content briefs that a local reviewer signs off on before anything goes live. We turn original-language demand and approved product facts into a market-native content plan. Before release, every page goes through native-language, factual, cultural, and search review.

Two specialists compare local search notes and approved product pages around a globe, while a third specialist sorts language cards into market groups.

Some of the 500+ brands we've worked with

See all references
  • GAP
  • Sporx
  • Odeabank
  • Joker
  • Yatsan
  • Turna.com
  • Amazon
  • BMW
  • Shell
  • Hyundai
  • PepsiCo
  • Red Bull
  • Decathlon
  • MediaMarkt
  • Bayer
  • Sanofi
  • EY
  • KPMG
  • GE
  • 3M
  • Domino’s
  • Lexus
  • Trendyol
  • Hepsiburada

We begin with the questions people ask in the market, keep every product claim connected to its source, and treat fluent writing as one review step rather than the final standard.

  1. Define the local page's role

    We set out the audience, available offer, intended action, excluded claims, supported locations, and source material for the target market. This shows whether there is a genuine local need or simply a request to reproduce the source site. The market, product, and legal owners confirm exactly which claims the local page may make before research begins.

    A market brief that explains what the page may answer, what it must not imply, and who approves product, legal, and language decisions.

  2. Research demand in the original language

    We gather local queries and representative result pages without treating translated seed terms as evidence. We retain the language, geography, device, date, result format, and uncertainty so reviewers can inspect the basis for each decision. A native-language reviewer confirms which clusters are a real local task. Translation artifacts and thin samples look identical in a spreadsheet.

    A local demand set organized around real tasks and result patterns, with ambiguous or limited clusters clearly marked.

  3. Map intent, terminology, and market differences

    We separate shared concepts from market-specific vocabulary, entities, offers, evidence needs, and user expectations. Product and market owners resolve questions that search data cannot answer on its own. The product and market owners decide whether each flagged difference changes a claim, an offer, or the evidence required.

    A localized intent map and approved terminology record showing which concepts transfer, which need to change, and which cannot be claimed in the market.

  4. Build native content briefs

    We assign each validated task to an owned page and specify the audience, questions, proof, claims, internal links, exclusions, and acceptance checks. Writers work from approved facts rather than filling gaps with plausible copy. The brief owner confirms every claim and proof point traces to an approved source before a writer opens the page.

    A market-native brief for every page that earns a separate place in the local site.

AI handles the volume; native and product reviewers decide what holds in this market.

AI prepares a first-pass market brief from the source-market page and the known legal or product exclusions, groups large original-language query exports by task, compares sampled result formats across thousands of rows in one pass, flags terminology, entities, and phrasing that differ from source-market language, and assembles the brief skeleton, internal-link candidates, and acceptance checklist. It does not decide what is true here. We do not present unreviewed machine translation as native-market expertise, we do not copy competitor language, examples, testimonials, or local proof into your plan, and we do not invent local availability, certification, or product parity.

These deliverables connect local demand with page ownership and approved language, making it clear what has been decided and where evidence is still missing.

  • Decision matrix

    Localized intent map

  • Playbook

    Terminology and claims record

  • Brief

    Market-native content briefs

  • Audit report

    Linguistic and factual QA log

We call it done when: The intent map, terminology record, content briefs, and QA log are done when every cluster traces to a real local task rather than a translated source keyword, every approved claim carries its evidence source, market availability, and review condition, every brief names its reviewer and publication condition, and every QA finding has a disposition and a named approver.

A new market usually needs its own search case, made locally. A translated version of the source-market page rarely holds up.

A good fit when

  • You have source-market content but no dependable view of how people in the target market describe the task, compare options, or expect a results page to help them.
  • Product availability, legal wording, cultural context, evidence, or terminology varies by market and must be settled before writers start drafting.
  • Several teams or agencies produce localized pages and need a shared intent map, terminology record, brief, and review trail.

Better handled as other work when

  • You only want to translate an English keyword list and publish it without researching local demand.
  • No one familiar with the language and market is available to review meaning, cultural fit, product facts, and the finished page.

If one of these is closer to your situation, start here instead: International SEO

We call it done when: An approved local page has a validated search task behind it, a named owner, claims tied to sources, a native brief, and a review decision on record. Pages with unsupported offers, limited local value, or unresolved wording do not go live.

  • Semrush

    collects original-language queries and representative local result pages

  • Google Keyword Planner

    compares local terminology without treating estimates as guaranteed demand

  • Google Trends

    checks regional wording and seasonality before briefs are assigned

  • AlsoAsked

    captures local follow-up questions that source pages may miss

  • Keyword Cupid

    clusters native queries into page tasks before localization begins

  • AccuRanker

    tracks approved local pages against their intended market queries

Bring your source pages, target markets, product facts, and research. We will identify the first decisions, evidence gaps, and review owners.
Discuss localization with Zeo

What can AI agents do in localization research?

They can group approved query exports, compare sampled results, flag terminology conflicts, and draft from controlled sources. A native specialist and the relevant product or market owner still decide meaning, claims, and release.

Why not translate the English keyword list first?

A translation can provide a research lead, but it does not demonstrate local demand. We study original-language queries and results before deciding which source concepts, offers, and page formats fit the market.

What happens if we do not yet have a native-language reviewer for the target market?

We pause the affected pages. Local research and terminology work may continue, but nothing is published until a named native-language reviewer approves the meaning, cultural fit, and product facts.

Can you reuse our source-market page structure for the local version?

Structure can carry over when the underlying task matches, but every claim, offer, and proof point still needs local evidence and owner approval before it enters a local page (a shared template does not skip that review).