What Are the Most Common GEO Mistakes, From Keyword Stuffing to Thin Content?
The most common GEO mistakes fall into five groups. Content is blocked or hidden from AI crawlers. Pages are thin, duplicated or stuffed with keywords. The third-party reviews and articles that AI answers rely on are ignored. Wrong facts about the business are left uncorrected. And progress is measured with one-off screenshots instead of repeated runs. Many also chase myths: special AI files, splitting content into "chunks", or publishing a page for every variation of a question. Google's own guidance says these are unnecessary, and the last can break its spam policies. The fixes are mostly unglamorous: make pages readable, answer real questions clearly, keep facts consistent, earn independent mentions, and measure properly.
What mistakes reduce a brand's visibility in AI answers?
Access mistakes
- Blocking AI crawlers by accident, through robots.txt rules, security plugins or CDN bot settings.
- Content that only appears after JavaScript runs, which most AI crawlers cannot see.
- Key information behind logins, forms or paywalls, such as pricing, specifications or research.
- Facts only in images or PDFs, such as price lists, menus and spec sheets.
- Accidental
nosnippetornoindextags, which remove pages or text from Google's AI features.
Content mistakes
- Thin pages that restate common knowledge without anything specific to your business.
- Many near-duplicate pages for slight variations of a question or location.
- Vague marketing copy instead of facts: "industry-leading solutions" rather than what you do, for whom, at what price.
- Answers buried under long introductions.
- Outdated facts on pages that still get cited.
- Pronoun-heavy writing that makes passages meaningless when quoted on their own.
Off-site mistakes
- Ignoring reviews, or collecting them only on one platform.
- Absent from the lists and articles engines cite for your category.
- Inconsistent business details across listings and profiles.
- Buying mentions or reviews, which platforms remove and regulators penalise.
Measurement mistakes
- Judging from one answer or one screenshot.
- Tracking brand-name questions and mistaking them for category visibility.
- Watching scores without reading the sources that explain them.
- Changing the question set every month, so nothing is comparable.
Strategy mistakes
- Treating GEO as separate from SEO, when most of the foundations are shared.
- Expecting quick results from recommendation work that takes months.
- Optimising for one engine only, when buyers use several.
Does keyword stuffing hurt visibility in AI search?
Yes, it does not help and can hurt. The original GEO research tested keyword stuffing alongside other content changes. It found stuffing did not improve visibility in generative answers, while adding statistics, quotations and citations did. Google treats keyword stuffing as a spam policy violation and has clarified that its spam policies apply to generative AI responses in Search too. There is also a practical cost: stuffed text is less clear, and AI engines quote clear, specific passages. Use the words buyers use, once each where they fit naturally, and spend the effort on answering the question.
Compare two openings for the same page. Stuffed: "Best emergency plumber Leeds. Our emergency plumber Leeds team is the best emergency plumber in Leeds for emergency plumbing in Leeds." Clear: "We handle emergency plumbing across Leeds 24 hours a day, usually arriving within 90 minutes, with a £95 call-out fee that covers the first hour." The second contains the same key terms once and gives an engine four facts it can quote.
What are the common GEO myths, and what does Google say about them?
Google's guide to optimizing for its generative AI features addresses several popular claims directly:
| Myth | What Google says |
|---|---|
| You need an llms.txt file or special AI markup | Google Search does not use llms.txt or similar files; you don't need new machine-readable files or markup to appear, including in its AI features |
| You should split content into small "chunks" for AI | You can ignore tactics like chunking content for Google Search |
| Creating mentions of your brand around the web helps | Pursuing inauthentic mentions is something you can ignore, and manipulation falls under spam policies |
| Publish a page for every way people might ask | Creating separate content for every variation, including fan-out queries, primarily to manipulate rankings or AI responses violates the scaled content abuse policy, and a high quantity of pages doesn't make a site better |
| Special schema gets you into AI Overviews | There are no additional technical requirements beyond being indexed and eligible to show a snippet |
| Adding or deleting lots of content makes a site look fresh | Google's helpful content guidance says this won't help |
Other engines have published less. Microsoft is the exception: its Copilot guidance recommends schema for products, reviews, FAQs and events, and clear, quotable sections. But tests found ChatGPT, Claude, Perplexity and Gemini read visible page text, not JSON-LD, when fetching pages, so schema is no substitute for clear visible facts. A related myth, that FAQ markup gets special treatment, lost its basis for Google when FAQ rich results were retired in May 2026.
What warning signs should beginners look for in AI search advice?
- Guarantees of being recommended or "ranking first in ChatGPT".
- Rankings language for AI answers, as if they were fixed lists rather than answers that vary between runs.
- Secret prompts or hidden text aimed at AI crawlers. Showing crawlers content that people cannot see, or that contradicts what they see, in order to manipulate rankings or AI answers, is cloaking.
- One tactic sold as the answer, whether schema, llms.txt or FAQ blocks.
- Proof from a single screenshot or a single client.
- Advice to create many pages targeting slight variations of a question.
- Buying reviews at all, or buying mentions and list placements without disclosure.
- No sources for statistics, or statistics without a date and method.
- Claims that SEO no longer matters. Most AI answers retrieve pages through search indexes.
Good advice is usually less exciting: it cites engine documentation or studies with stated methods, admits uncertainty, and focuses on content quality, access, reviews and measurement.
How do you fix the most common mistakes?
- Audit access: robots.txt, CDN settings, rendering and snippet tags on key templates.
- Consolidate thin and duplicate pages into strong pages that answer each question once.
- Rewrite the openings of your most important pages to answer directly with specific facts.
- Correct facts on your site, listings and profiles, and track which wrong statements engines repeat.
- Map the third-party sources cited for your questions and work to be present in them.
- Set up a fixed question set and measure across repeated runs each month.
Whether a GEO tactic actually works can be tested with a control group, as explained in what GEO tactics can improve AI citation share and how to test them. Whether GEO work can harm SEO is covered in whether GEO work hurts traditional SEO rankings.
What do people ask about GEO mistakes?
Can GEO mistakes get a site penalised?
Tactics that break spam policies, such as scaled content abuse, cloaking or keyword stuffing, can lead to lower rankings or manual actions in Google, which also affects its AI features.
Is adding FAQs to every page a mistake?
It is when the questions are forced or repeated across pages. FAQs help where they answer real, page-specific questions.
Is it a mistake to write content with AI tools?
Not in itself. The mistake is publishing generic, unedited AI text without the specific facts and experience that make content worth citing.
What is the single most common mistake?
In practice, content that says too little that is specific: no prices, no details, no evidence. Engines cannot recommend what they cannot describe.
Published by The Kovmere Team · updated Sep 29, 2026 · More resources