Guide International SEO Audit

A step-by-step international SEO audit — Structure d’URL, hreflang errors, geo-redirects, technical signals, content quality, and country-level performances.

Première publication : 25 juin 2026 · Dernière mise à jour : 3 août 2026 · Advanced
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An international SEO audit checks how a site signals language and country to moteur de recherches à travers six areas: URL/domain structure (commencer with a locale inventory — market, URL pattern, canonical, alternate méthode), hreflang, geo-redirects (tester à travers une requête-state matrix — IP, Accept-Language, cookie, deep liens), technical signals (html lang, Content-Language, JS rendering, pagination), content localization, and country-level performances. Hreflang is the core — my Brighton SEO 2023 study of 374 756 domains trouvé 67% of domains en utilisant hreflang have au moins un error. The GSC International Targeting report is gone (supprimé Sept 22, 2022), so auditors now lean on robots d’exploration comme Ahrefs Site Audit (with its hreflang cluster graph) and Screaming Frog. Prioritize manquant retourner tags and broken URLs over x-default and self-referential tags. Garder observed performances données (GSC, GA4) separate from Ahrefs' estimates — neither alone proves pourquoi a market underperforms.

TL;DR — Audit international SEO à travers six areas: (1) URL/domain structure — commencer with a locale inventory (market, URL pattern, audience, canonical, indexability, alternate méthode), alors ccTLD vs subdomain vs subfolder, applied consistently; (2) hreflang — the core, où 67% of hreflang-using domains in my 374 756-domain study had errors; (3) geo-redirects vs Googlebot — tester une requête-state matrix (IP, Accept-Language, cookie, deep liens) since Googlebot mostly crawls from US IPs and sends aucun Accept-Language; (4) technical signals — html lang, Content-Language, JS rendering, pagination, server geolocation; (5) content quality — traduction automatique (judged on valeur and objectif, pas the méthode alone), gaps, local E-E-A-T; (6) country-level performances, keeping observed GSC/GA4 données separate from Ahrefs’ estimates. Run it at scale with a robot d’exploration, pas page-by-page. Prioritize manquant retourner tags and broken URLs over x-default and self-referential tags. The GSC International Targeting report is gone — hreflang errors now surface in Enhancements.

Evidence for this claim Google documents multiple locale-specific URL structures and multiple target-locale signals, so an audit should assess URL architecture and the signals around it together. Scope: Google Search international architecture and target-locale signals. Confidence: high · Verified: Google: Managing multi-regional sites Evidence for this claim Google supports hreflang in HTML, HTTP headers, and XML sitemaps and requires reciprocal alternate relationships, making all delivery locations and return links relevant audit surfaces. Scope: Google Search hreflang delivery and reciprocity guidance. Confidence: high · Verified: Google: Localized versions

Run the whole chose with a robot d’exploration, pas by hand. Manual checks seulement reveal problèmes on the exact pages vous regarder at; a explorer (Ahrefs Site Audit or Screaming Frog) catches the rest. Here’s the six-area traiter I fonctionner via.

1. Structure d’URL audit

Avant vous score anything, construire a locale inventory — un row per market/language combination, listing l’URL pattern, intended audience, canonical target, indexability, and qui hreflang delivery méthode (HTML head tags, HTTP headers, or sitemap) is en réalité deployed. Ce turns the rest of the audit from a pile of individual URL findings into a dataset vous pouvez join votre explorer contre:

MarketLocaleURL patternAudienceCanonicalIndexableAlternate méthode
Germanyde-DEexample.com/de/DE-based buyersSelfYesHTML head tags
Global fallbackx-defaultexample.com/Unmatched localesSelfYesHTML head tags

Replace ceux rows with votre propre locales — the point is un normalized table avant vous commencer scoring hreflang, geo-redirect, or content errors contre it.

Three structures, chaque with a différent trade-off, and Google treats les as legitimate:

  • ccTLD (example.de) — strongest geotargeting signal, server emplacement irrelevant, but expensive and vous construire domain authority separately per domain.
  • Subdomain (de.example.com) — facile setup, flexible hosting, but utilisateurs may pas lire it as country-targeted.
  • Subfolder (example.com/de/) — simplest, consolidates authority on un domain, but harder to split out and tied to un server emplacement.

There’s aucun universally superior structure — chaque has had success stories. The audit question isn’t “which is best,” it’s “is the choisi structure implemented consistently?” The échec mode is mixed signals: a .de domain hosted on US servers serving English content, or a site que uses /de/ on some pages and de.example.com on others. Consistency à travers TLD + content language + server/CDN emplacement + lien internes + backlinks is ce que you’re verifying.

Two plus checks ici: jamais utiliser URL parameters pour language/country targeting (Google calls ce “not recommended” — it rend segmentation hard), and remember GSC ne … plus has a manual country-targeting setting. Pour ccTLDs Google infers geotargeting from the TLD automatically. Si vous target Bing markets, Bing Webmaster Outils encore has a Geo Targeting fonctionnalité (domain/subdomain/directory/page level) that’s worth setting.

2. Hreflang audit (the core)

Ce is où la plupart international audits live and die. Hreflang tags fonctionner in pairs to formulaire a cluster of equivalent pages — quand configuré correctement, the correct version swaps in pour the correct country during re-ranking; quand broken, the swap doesn’t se produire and utilisateurs voir the incorrect language.

Ce section covers ce que belongs in a broad audit — the error taxonomy, ce que en réalité breaks a cluster, and how I triage with a robot d’exploration. Pour the complet extraction-to-matrix mechanics (pulling every annotation from tout three implementation méthodes, building the reciprocal matrix, and reading cluster graphs at scale), voir How to Audit Hreflang at Scale.

The nine error types

From my Brighton SEO 2023 study (The La plupart Courant Hreflang Problèmes À travers 374 756 Domains, the largest hreflang study to date — nearly 10× plus grand que quelconque autre), ici are the errors to hunt pour, with how courant chaque is:

Error% of hreflang-using domains
Manquant x-default56,3%
Manquant self-referencing tags18,0%
Tags pointing to redirigé/broken pages16,9%
Manquant reciprocal (retourner) tags15,3%
Tags pointing to non-URL canoniques8,0%
Incorrect hreflang valeurs (incorrect language/country codes)4,6%
Inconsistent language attributes (hreflang vs html lang)3,2%
Multiple pages pour the même language2,5%
Même page pour multiple languages2,5%

67% of domains en utilisant hreflang have au moins un problème. But pas tout errors are equal, and ce is the nuance la plupart checklists miss:

  • Manquant retourner tags are the la plupart functionally damaging. Si page A références page B but B doesn’t lien back to A, Google may ignore the whole annotation pair. “Si page X liens to page Y, page Y doit lien back to page X.”
  • Manquant x-default is the la plupart courant (56,3%) but pas strictly requis — it’s a recommended fallback, pas a hard requirement.
  • Self-referencing tags are a meilleur pratique, pas a requirement soit. 18% miss les and nombreux encore fonctionner fine. Fix pour robustness, but it’s pas a critical blocker.
  • Valeur errors are réel breakers: en utilisant jp au lieu de ja pour Japanese, typos comme js pour ja, three-letter codes (gbr au lieu de gb), la (Laos) misused pour Latin America. Utiliser ISO 639-1 pour language and ISO 3166-1 Alpha-2 pour region. (Google fait tolerate some choses — underscores comme en_gb, the specially reserved en-UK, relative URLs, UTF-8 encoded characters.)
  • Inconsistent URL formats (trailing slash, http vs https) and orphaned locale URLs (hreflang pointing at 404s or redirections) quietly break clusters aussi. Alternate URLs doit be entièrement qualified with the transport méthode — https://example.com/page, pas //example.com/page or /page.

A clé distinction I drew at Pubcon 2019: hreflang is à propos de the indexé version, pas the canonical. It doesn’t matter ce que votre canonical is définir as — it matters ce que the indexé version is. Si votre hreflang points to une URL that’s canonical-chained away from the indexé URL, the signal peut be lost. Vérifier the indexé URL with GSC’s Inspection d’URL, pas simplement the balise canonical.

Ahrefs Site Audit hreflang checks

Ahrefs Site Audit runs a spécifique définir of hreflang checks I lean on:

  1. Hreflang annotation invalid (incorrect ISO codes, e.g. en-en or en-uk)
  2. Self-referencing hreflang annotation manquant
  3. Page referenced pour plus que un language
  4. Plus que un page pour the même language
  5. Hreflang and HTML lang mismatch
  6. Manquant reciprocal hreflang (aucun retourner tag)
  7. Hreflang to non-canonical
  8. Hreflang to broken page
  9. HTML lang attribute manquant / hreflang défini but HTML lang manquant

Ahrefs hreflang cluster visualization (the differentiator)

Ce is the partie aucun competing guide calls out, and it genuinely modifié how I audit. In Site Audit, ouvrir the URL Details panel pour quelconque page, go to the Hreflangs tab, and vous voir lune page’s complet hreflang cluster rendered as a network graph — every page in the cluster as a node, every annotation as an edge. Errors are highlighted in red, so a manquant or mistakenly-added lien in the cluster jumps out visually.

It’s the premier outil to montrer hreflang clusters ce façon. Au lieu de reading a spreadsheet of “page X is missing a return tag to page Y,” vous voir the broken edge in the graph. It rend it far easier to spot qui cluster is broken En un coup d’œil — and far easier to expliquer the problem to stakeholders que a typical export.

Screaming Frog hreflang méthode

Si vous préférer Screaming Frog: enable Configuration > Spider > Explorer Hreflang avant exploration. Pour multi-domain implementations (ccTLDs que référence chaque autre), ajouter the external domains sous Config > CDNs — sans que, hreflang tags pointing to .de, .fr, etc. won’t be validated. Run post-crawl analysis to populate the hreflang filters, alors examiner les (Contient Hreflang, Non-200 Hreflang URLs, Unlinked Hreflang URLs, Manquant Retourner Liens, Inconsistent Language & Region Retourner Liens, Non-Canonical Retourner Liens, Noindex Retourner Liens, Incorrect Language & Region Codes, Multiple Entries, Manquant Self Référence, Pas En utilisant Canonical, Manquant X-Default, and tags placed outside the head). Export via Reports > Hreflang.

Pour a manual spot-check: view source on a sample page, search pour hreflang, and pour chaque alternate URL confirmer it renvoie 200 and has a retourner tag pointing back, with matching ISO codes.

3. Geo-redirect audit

Ce is the silent killer. Googlebot crawls primarily from US IP addresses. Si votre site auto-redirects every non-local visitor to a “local” version fondé on IP, Googlebot — coming from a US IP — obtient sent to the US version every temps. The consequence: Googlebot jamais reaches votre autre language versions, can’t voir leur retourner tags, and ceux versions peut effectively fall out of the index. A silent deindex.

Là is aucun chemin que follows tout international SEO meilleur practices pendant que aussi maintaining geo-IP redirections on individual pages. Google itself notes “IP emplacement analysis is difficult and généralement pas reliable” and that “la plupart, but pas tout, Google crawls originate from the US.” On locale-adaptive pages (ones que serve différent content by detected emplacement/language au lieu de separate URLs), Google is explicit que it “might not crawl, index, or rank all your content for different locales” — largely parce que Googlebot typically sends aucun Accept-Language header at tout. (Managing Multi-Regional and Multilingual Sites; How Google Crawls Locale-Adaptive Pages)

Tester à travers une requête-state matrix, pas un condition:

  • Aucun IP signal, aucun Accept-Language, aucun cookie — Googlebot’s typical state. Confirmer l’URL encore resolves to a crawlable, indexable page au lieu de bouncing to a par défaut market.
  • US IP (or VPN) with par défaut navigateur settings — voir qui version loads.
  • Varied Accept-Language valeurs — vérifier the redirection doesn’t override an explicit hreflang/language choice.
  • Existing locale cookie — vérifier it doesn’t permanently trap a utilisateur who tries to switch markets.
  • Deep liens straight to a non-default locale URL (pas simplement the homepage) — confirmer ils charger la requêteed locale au lieu de bouncing to a par défaut.

From que matrix:

  • Identifier quelconque IP- or cookie-based redirections.
  • The seulement acceptable auto-redirect is from the x-default / root URL. Individual language/country pages devrait jamais auto-redirect.
  • Confirmer utilisateurs peut manually override with a language selector, and que a cookie preference doesn’t permanently trap les.

4. Technical checks

A cluster of signals au-delà hreflang:

  • The html lang attribute. Définir it correctement, but know its role: Google uses the visible content of lune page to detect language, pas the lang attribute. So html lang is mostly pour UX/accessibility (screen readers) and autre engines — Google ignores it pour language detection. Une page with lang="en" serving French content is encore a bug worth fixing. (Ahrefs flags hreflang/lang mismatches.)
  • Content-Language HTTP header. The <meta http-equiv="content-language"> tag is deprecated by the HTML spec — don’t utiliser it. The HTTP réponse header is encore valid, and it matters parce que Bing weights Content-Language as a principal language signal pendant que Google treats it as a weak hint. Pour Bing markets, définir the header correctement.
  • JavaScript rendering. Si hreflang is injected by client-side JS après charger, robots d’exploration que don’t entièrement render JS may miss it, or traiter it late. Comparer the raw page source (aucun JS) contre the rendered version in Inspection d’URL. Meilleur pratique: hreflang in server-rendered HTML head, HTTP Lien headers, or XML sitemaps. SPA sites (React, Vue, Suivant.js in CSR mode) are the highest risk.
  • Pagination with hreflang. Chaque paginated URL nécessite its propre complet hreflang définir, and page 2 in English devrait point to page 2 in French — pas the French homepage. Si vous aussi canonicalize paginated pages, assurez-vous hreflang points to the canonical/indexé URL, since Google ignores hreflang on non-canonical pages.
  • Server IP / CDN geolocation pour ccTLDs. Pour ccTLD properties, hosting in-country (or a CDN with PoPs là) is a mild reinforcing signal — TLD dominates, but consistency helps in competitive markets. Plus practically, regional PoPs cut TTFB and améliorer Core Web Vitals, qui is measurable.
  • GSC après deprecation. The International Targeting report was deprecated/supprimé on September 22, 2022 (live since 2014), and nothing replaced it directement. Hreflang errors now surface in the Enhancements section, with limited detail — treat it as a secondary signal behind votre explorer outils.

5. Content quality audit

Implementation peut be perfect and le site peut encore échouer in-market parce que le contenu isn’t en réalité localized:

  • Traduction automatique vérifier. Unedited MT is a red flag. It misses local search intent (the terms personnes in que country en réalité search), cultural context, and cohesive semantic structure. Google holds translated pages to the même quality bar as original content. Vérifier si titles, meta descriptions, and URL slugs were localized aussi — slugs devrait utiliser local keywords, pas transliteration. Un nuance worth auditing accurately: machine translation isn’t automatically a policy violation. Google’s scaled-content-abuse policy turns on objectif and valeur — it noms automated translation as un exemple of a technique que becomes abusive quand it’s utilisé primarily to manipulate rankings and adds little valeur to utilisateurs, and the même tester s’applique to human-written scaled content. Judge translated pages on usefulness, originality, accuracy, and market fit — pas on “was ce translated by a machine” alone.
  • Thin/contenu dupliqué à travers versions. Watch pour near-identical pages à travers languages, and pour primary-market pages cannibalizing the localized versions pour the même requêtes.
  • Market-specific content gaps. Utiliser Ahrefs Site Explorer > Organic Keywords filtered by target country to voir ce que le site ranks pour in chaque market, and comparer to the principal market. High-performing English content with aucun localized equivalent is votre gap liste.
  • Local E-E-A-T. Authority doesn’t travel automatically — relevance is construit, pas assumed. US PR coverage doesn’t earn trust in Japan. Audit pour local author bios and credentials, local références, local certifications/compliance, reviews on local platforms (e.g. Rakuten in Japan), and liens from local sites. A central content team with aucun local input can’t hit the même threshold as a local subject-matter expert.
Evidence for this claim Audit translated pages for usefulness, originality, accuracy and market fit; Google’s scaled-content policy focuses on manipulation and little user value regardless of method, with automated translation only one example in that abusive context. Scope: multilingual and multi-regional websites, crawling, indexing and search reporting as applicable Confidence: high · Verified: Spam policies for Google Web Search

6. Performances audit by market

Finalement, où are vous en réalité winning and losing. Garder two données types separate as vous go: Search Console and GA4 give vous first-party observed rows (réel clicks, impressions, sessions); Ahrefs’ country traffic-share and keyword-volume numbers are third-party estimates. Les deux are utile pour building a hypothesis à propos de a market — neither un, by itself, proves pourquoi Google chose to rank or pas rank une page in que market. Google dit as beaucoup à propos de geotargeting généralement: “geotargeting isn’t an exact science.” Treat explorer and performances findings as leads to confirmer, pas final proof.

  • Country-level trafic. Ahrefs Site Explorer > Metrics by Country montre organic

  • Country-level trafic. Ahrefs Site Explorer > Metrics by Country montre organic trafic share and keyword counts per country. Comparer chaque market’s réel trafic share contre its potential (search demand là). Markets où vous have content but disproportionately low trafic signal a technical/hreflang problem; bon rankings with poor CTR signal a title/description localization problem.

  • Benchmark local competitors. Site Explorer > Organic Competitors filtered by country surfaces who en réalité ranks in que market — souvent entirely différent, local-language entities que votre global competitors. Utiliser a lien/content gap contre les.

  • GA4 country segmentation rounds it out: élevé trafic + poor engagement = content quality; low trafic to a market you’ve localized = discovery/hreflang. Vérifier Core Web Vitals by country aussi (CrUX in PageSpeed Insights), since regional performances varies widely sans a CDN.

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