Does Google struggle to index certain oral languages?

Which languages are affected by this indexing problem?

We’re talking about traditionally oral languages — think of indigenous languages from North America, some languages from Sub-Saharan Africa, Polynesian languages, or regional dialects that have only recently been transcribed. These idioms have been codified in writing for cultural preservation reasons, often by linguists or activist communities, but they have not evolved naturally into a standardized written form over centuries.

The difference with French, English, or Chinese? The latter have developed stable spelling conventions, standardized punctuation, and, importantly, a massive written corpus that allows algorithms to learn linguistic patterns. For a recently transcribed oral language, Google lacks raw material: few reference texts, multiple competing writing systems at times, and a fuzzy written grammar.

Why does Google consider these languages to be ‘technically difficult’?

Modern search engines rely on natural language processing (NLP) models trained on vast amounts of text. To function properly, these models need to detect patterns: word segmentation, named entity recognition, syntactic parsing, semantic disambiguation. With a transcribed oral language, these patterns are either absent or inconsistent.

In concrete terms, if a language only has a few thousand indexed pages versus billions for English, the algorithm lacks enough signal to build a reliable model. Worse: if multiple communities use differing spelling conventions for the same language (think of the dialectal variations in Breton or Navajo), Google ends up with fragmented corpora that don’t allow for coherent model training.

What does it mean to 'index and store' without guaranteed ranking?

Gary Illyes admits that Google tries to index this content — in other words, Googlebot crawls the pages and stores them on its servers. But indexing doesn’t mean relevant ranking. A page can be technically indexed without ever appearing in search results, lacking exploitable quality signals.

For an SEO practitioner, this is a critical nuance. You can check indexing via site: or Search Console, see that your URLs are indexed… and observe zero organic traffic. If your content is in a language that Google doesn't algorithmically understand, the ranking mechanisms (BERT, MUM, passage ranking) simply don’t work — or work very poorly.

• Insufficient corpus: Less text available = failing NLP models
• Non-standardized spelling: Dialectal variations that fragment the signal
• Indexing ≠ ranking: Pages stored but invisible in the SERPs
• No quick solutions: Google is “trying” but guarantees nothing in the short term
• Real SEO impact: Niche multilingual content can go orphaned in the index

Is this statement consistent with field observations?

Let’s be honest: yes, and this can be easily verified. SEOs working on sites in minority languages regularly report erratic behavior in Search Console — indexed pages that never get served, broad queries that trigger no results, snippets completely out of context. This isn’t a bug; it’s a structural limitation of Google’s algorithms faced with languages for which they don’t have enough training data.

I have personally observed sites in Basque or Corsican with correct indexing rates (80-90% of URLs in the index) but an almost zero organic CTR. The reason? Google does not understand the fine semantics of these languages, so it cannot match search intentions with content. The engine resorts to simplistic criteria: exact match of keywords, technical signals, backlinks — but without the layer of linguistic understanding that makes the difference.

What nuances should be added to this statement?

Gary Illyes remains deliberately vague. He talks about “languages that are not really designed to be written” — but how many languages exactly? A few dozen? Several hundred? And what specific criteria trigger this algorithmic limitation? Number of speakers? Volume of indexed text? Existence of a validated reference corpus?

Without these details, it's impossible to know if your multilingual project will hit this wall. Is a site in Gascon Occitan affected? And what about a site in Guadeloupean Creole? [To be verified] — Google does not provide any list, diagnostic tools, or quantitative thresholds. We are navigating blind, with only empirical performance observation in Search Console as our compass.

Another point: Google says it’s “trying” to index this content. But with what priority? If the crawl budget is limited and the algorithm detects a “difficult” language, will it reduce the frequency of Googlebot's visits? Will it deprioritize these pages in rendering? Nothing is said, and this is concerning for planning an SEO strategy for these languages.

In what cases does this rule not apply?

If you manage a classic multilingual site — French, English, Spanish, German, Japanese, Chinese — you are absolutely not affected. These languages have massive corpora, mature NLP models, and Google has managed them without difficulty for years. The problem is limited to languages with low volumes of digital content and/or unstable spelling.

It's also important to distinguish minority languages with an active digital community (like Welsh, which benefits from public investment in web content creation) from those that only exist through a few cultural preservation sites. The more signal there is, the better Google improves its models — it’s a virtuous cycle. A language can thus gradually “emerge” from this gray area if its digital footprint grows.

What to do if your site targets a potentially affected language?

First step: objectively diagnose the situation. Check in Search Console the indexing rate, the volume of queries generating impressions, and especially the average position of your pages. If you have 500 indexed pages but 0 impressions over 90 days, it’s likely a signal that Google isn't ranking your content due to a lack of linguistic understanding. Compare with an equivalent site in a mainstream language: the gap will tell you if you are impacted.

Then, anticipate that the classic SEO levers may not work as usual. Fine semantic optimization, semantic cocooning, topic clustering — all rely on Google’s ability to understand the relationships between concepts. If the algorithm does not master your language, these techniques lose effectiveness. It’s necessary to return to more fundamental basics: impeccable technical structure, correct hreflang tags, quality backlinks, and especially strong brand signals (direct searches, recurring traffic) that compensate for the weakness of organic ranking.

What mistakes to avoid in this specific context?

Do not embark on a massive content strategy without first validating that Google correctly indexes and ranks your initial pages. Too many projects spend resources producing hundreds of articles in a minority language, only to discover six months later that Google never serves them in results. First, test with a reduced sample, analyze actual performance, and then scale if metrics are satisfactory.

Another trap: relying solely on SEO to acquire traffic. If Google struggles to rank your content, you need to diversify your channels — social media (in the target language), newsletters, partnerships with cultural institutions, SEA if the search volume justifies the investment. SEO becomes one channel among others, not the cornerstone of your acquisition strategy.

How to maximize your chances despite these limitations?

Focus on absolute technical quality: impeccable loading times, mobile-first, comprehensive Schema.org markup (even if Google doesn’t fully utilize it, it doesn’t cost anything to do it correctly). Also strengthen the off-page signals: backlinks from recognized sites in your linguistic domain, mentions in specialized media, presence on Wikipedia in the target language if possible.

If your budget allows, consider creating an alternative version of the content in a better-supported language (English, French…) with a clean translation system and hreflang tags. This gives you a functional SEO entry point, and you can then redirect users to the version in their native language via intelligent UX. It’s a detour, but sometimes it’s the only way to gain organic traffic.

• Check the indexing rate AND the volume of impressions in Search Console
• Test with a sample of content before scaling production
• Prioritize technical fundamentals: speed, mobile, structure
• Strengthen brand signals (direct searches, recurring traffic)
• Diversify acquisition channels (social media, partnerships, email)
• Consider an alternative version in a better-supported language with hreflang