DEV Community: Watson Foglift

We Ran Our Own GEO Tool Against Our Own Site — Here's What We Found

Watson Foglift — Tue, 07 Apr 2026 21:07:54 +0000

Our tool gave us a perfect GEO score. Our content was still full of unsourced claims.

We built Foglift to help sites optimize for AI search engines — ChatGPT, Perplexity, Google AI Overviews. It scans your site and flags technical gaps: missing schema markup, robots.txt issues, structured data problems.

So we pointed it at ourselves. The automated scan came back with SEO 100, GEO 100, AEO 88. Three performance warnings. That's it.

Then we actually read our blog posts. What we found was embarrassing.

The problem automated scans don't catch

Our 9 pillar blog posts — the ones driving most of our organic traffic — were full of the exact patterns we tell our users to avoid:

Unsourced statistics. Our GEO vs SEO comparison claimed "60-70% overlap between Google and ChatGPT results." No source. We'd picked that number up from a vendor blog that also had no source.
Outdated data presented as current. We cited Google's daily search volume as 8.5 billion. The 2026 DemandSage data puts it at 13.7 billion+.
Recycled vendor marketing claims. The widely-shared "44% increase in AI citations from schema markup" stat from BrightEdge? We repeated it. But the actual BrightEdge article doesn't contain that number — it describes structured data improving AI feature inclusion, not a 44% citation lift. We had never checked the primary source.

No automated scanner catches this. You have to read the content.

What we actually found in 9 blog posts

We went through every pillar post and cataloged the problems. Here's the pattern:

Issue	Count across 9 posts	Example
Stats with no source	14	"68% of companies haven't started GEO"
Outdated numbers	6	Google searches: 8.5B → actually 13.7B+
Vendor claims presented as research	5	"44% schema citation lift" (unsourced)
Missing Sources section	9 of 9	Zero posts had a references section
"Studies show" with no study named	8	"Studies show AI prefers structured data"

Every single post had at least two of these problems. Our most-shared post — How ChatGPT Ranks Websites — had five unsourced claims in the first 500 words.

The fix: honest evidence over marketing claims

We spent 7 sessions upgrading all 9 posts. The process for each was the same:

Find primary research. For every claim, we tracked down the original study — not the blog post that cited it, not the infographic that summarized it. The actual paper or report with methodology and sample size.
Replace or remove unsourced claims. If we couldn't find a primary source, we either removed the stat or flagged it as unconfirmed.
Add honest evidence callouts. Where vendor claims were exaggerated or unverifiable, we said so explicitly — including for popular stats we'd previously repeated ourselves.
Add a Sources & Further Reading section. Every post now cites 6-12 original sources with author, title, year, and sample size where available.

Here's what replaced the unsourced claims:

Before (unsourced)	After (cited)
"60-70% overlap between Google and ChatGPT"	Chatoptic study: 62% URL overlap, but only 0.034 rank correlation (1,000 queries, 15 brands)
"68% haven't started GEO"	Incremys 2026: 34% of companies have trained teams in GEO; 63% of marketers prioritize generative search
"44% citation lift from schema"	Google & Microsoft confirmed schema for AI features (March 2025); ChatGPT/Perplexity/Anthropic have not confirmed. Actual empirical data is mixed.
"Studies show freshness matters"	Seer Interactive: 71% of ChatGPT citations come from 2023-2025 content. Digital Bloom: updating within 30 days = 3.2x more citations.
"AI search is growing fast"	McKinsey (Aug 2025, 1,927 consumers): 44% prefer AI search. Bain 2025: 80% of search users rely on AI summaries ≥40% of the time.

The schema markup post became our template for this approach. We wrote an explicit callout box: "What the research actually shows (2024-2026)" — separating what's confirmed by Google/Microsoft, what's not confirmed by ChatGPT/Perplexity, and what the empirical data actually says. Nuance that no other vendor blog in this space bothers with.

What we learned that surprised us

1. Most "GEO stats" trace back to 2-3 vendor reports, heavily paraphrased. We found the same BrightEdge and Gartner numbers recycled across dozens of blogs, each time with slightly different framing and less context. The telephone game makes every stat less accurate.

2. The largest study is barely cited. SE Ranking and Search Engine Journal analyzed 129,000 domains and 216,524 pages across 20 niches — the biggest ChatGPT citation study to date. Key findings: expert quotes increase citations from 2.4 to 4.1; 19+ data points increase citations from 2.8 to 5.4; referring domains are the single strongest predictor. We found this study referenced in maybe 5% of the "how to optimize for AI" articles we surveyed.

3. Honest uncertainty earns more trust than false confidence. Saying "this isn't confirmed" is more valuable than confidently citing an unverifiable stat. The schema markup post that explicitly calls out what's unconfirmed has become one of our most-linked pieces.

4. The research bar is low. Adding primary sources to a blog post in this space immediately puts you in the top 10% of content quality. Most vendor blogs in GEO/AEO cite each other, not the research. The bar for being the honest-evidence source is surprisingly achievable.

What this means for developers building content

If you're writing technical content for SEO or AI search visibility:

Trace every stat to its primary source. If you can't find the original study with methodology and sample size, flag it as unverified or drop it.
Add a Sources section. Academic-style — author/org, title, year. This is table stakes in research but rare in tech content.
Say "not confirmed" when it's not confirmed. AI companies are opaque about ranking factors. Honesty about uncertainty is a competitive advantage.
Cite the actual sample sizes. "A study of 129,000 domains" carries more weight with both humans and AI models than "research shows."
Update stats every 3-6 months. We had 2024 numbers presented as current on a page dated 2026. AI models weight freshness heavily — 71% of ChatGPT citations come from content published 2023-2025.
Run your own tools on yourself. The automated scan was a useful starting point. The real value came from the manual content audit it prompted.

Where we stand now

After the 9-post upgrade, our site scans at Overall 95, SEO 100, GEO 100, AEO 88. The AEO gap is performance-related (server response time), not content.

Every blog post now has 6-12 cited sources. Zero unsourced "studies show" claims remain.

Foglift is free — if you want to run the same scan on your own site, it takes about 10 seconds. But the real audit starts when you read your own content with fresh eyes and ask: "Where did this number actually come from?"

That's the question that fixed our content. It'll probably fix yours too.

Built by the Foglift team. We scan for GEO + AEO readiness so AI search engines actually cite you. Currently scoring ourselves at 95 — the remaining 5 points are a performance problem we're still working on.

What Actually Makes AI Search Engines Cite Your Website (The Research Data)

Watson Foglift — Mon, 06 Apr 2026 07:20:23 +0000

Google and ChatGPT don't agree on who deserves to rank.

A 2025 Chatoptic study tested 1,000 search queries across 15 brands and found just 62% overlap between Google's first-page results and ChatGPT's cited sources. The correlation coefficient between Google rank and ChatGPT visibility? 0.034 — essentially zero.

That means your SEO playbook isn't enough anymore. AI search engines — ChatGPT, Perplexity, Gemini, Google AI Overviews — use fundamentally different ranking signals. And with Bain reporting that 80% of search users now rely on AI summaries at least 40% of the time, this isn't a niche concern.

I've spent the last few months digging through every major study on AI search citation behavior. Here's what the data actually says.

The biggest study: 129,000 domains analyzed

SE Ranking and Search Engine Journal published the most comprehensive analysis of ChatGPT citation patterns to date — 129,000 domains, 216,524 pages, across 20 industry niches.

Their key findings:

Signal	Impact on AI Citations
Expert quotes in content	4.1 vs 2.4 citations (+71%)
19+ statistical data points	5.4 vs 2.8 citations (+93%)
Articles over 2,900 words	5.1 vs 3.2 citations (+59%)
Content updated within 3 months	6.0 vs 3.6 citations (+67%)
350K+ referring domains	8.4 vs 1.6 citations (+425%)
Structured data + FAQ schema	+44% more AI citations

The takeaway: data density and authority signals matter far more than keyword optimization.

ChatGPT only cites about 15% of the pages it retrieves. The top 10 domains capture 46% of all citations. If your content doesn't stand out with verifiable data and expert credibility, it gets ignored.

The foundational GEO research (10,000 queries)

The term "Generative Engine Optimization" comes from an academic paper by Aggarwal et al. presented at KDD 2024 (the top data mining conference, organized by ACM SIGKDD). Researchers from Princeton and IIT Delhi tested 10,000 queries across 9 domains to measure what actually improves visibility in AI-generated responses.

Their results:

Optimization Technique	Visibility Change
Adding quotations from experts	+41%
Adding statistics with sources	+33% (+37% on Perplexity)
Citing authoritative sources	+30% (+115% for lower-ranked sites)
Improving fluency	+28%
Using technical terminology	+18%
Keyword stuffing	-10% (hurts you)

The +115% for citing sources on lower-ranked sites is the most interesting finding. It means smaller sites benefit disproportionately from source attribution — AI models reward citation behavior more heavily when the domain itself isn't already an authority.

Who gets cited? The authority distribution is brutal

BrightEdge found that the top 50 brands capture 28.9% of all AI mentions, while 26% of brands receive zero AI visibility.

But it's not just about brand size. The citation sources are different from what you'd expect:

Wikipedia: 47.9% of ChatGPT citations (Aggarwal et al.)
Reddit: 46.7% of Perplexity citations
Brand-owned websites: Only 5-10% of AI sources (McKinsey, Aug 2025)

That last stat is the wake-up call. 90%+ of AI search sources come from publishers, user-generated content, and review platforms — not from your own website.

This means your off-site presence matters enormously. Forum discussions, third-party reviews, guest posts on authoritative publications — these feed the AI models more than your own blog does.

Content freshness: the 30-day window

One of the most actionable findings: Digital Bloom's analysis of 7,000+ AI citations found that content updated within 30 days gets 3.2x more AI citations.

Seer Interactive corroborated this — 71% of ChatGPT citations come from content published between 2023-2025, with 31% from 2025 content alone.

The practical implication: if you wrote a great technical article in 2022 and haven't touched it since, AI search engines are probably ignoring it. Even minor updates — refreshing statistics, adding recent examples, updating dates — can dramatically improve citation probability.

The conversion difference is real

So does any of this matter for business outcomes?

Seer Interactive tracked ChatGPT referrals over 7 months: 15.9% conversion rate vs. 1.76% for Google organic (9x higher)
Similarweb found AI referral conversions at 11.4% vs. 5.3% for organic search
Ahrefs reported AI search visitors = 0.5% of traffic but drove 12.1% of signups

AI search traffic is small in volume but absurdly high in intent. People asking AI models for recommendations are further down the funnel than people typing broad Google queries.

What developers should actually do

Based on the research, here's what moves the needle:

1. Add data to everything you publish

The SE Ranking data is unambiguous: pages with 19+ statistical data points get nearly double the AI citations. Don't write "performance improved significantly" — write "P95 latency dropped from 340ms to 89ms after switching to connection pooling."

2. Quote experts (or be the expert being quoted)

Expert quotes in content = +71% more citations. If you're writing a technical article, cite the source's author by name. If you're building a project, get quoted in other people's content.

3. Update content every 30 days

The 3.2x citation boost for recently-updated content is the easiest lever to pull. Set a calendar reminder to refresh your key pages monthly.

4. Build off-site presence

With 90%+ of AI sources being third-party content, your own blog is necessary but not sufficient. Contribute to Stack Overflow, write on Dev.to, get mentioned in listicles, earn Reddit discussion.

5. Use structured data

FAQ schema, comparison tables, and how-to markup increase AI citation rates by 40-44%. These are one-time implementations with compounding returns.

6. Don't keyword stuff

The GEO research showed keyword stuffing reduces visibility by 10%. AI models penalize content that optimizes for crawlers rather than readers.

Checking your own AI visibility

We built Foglift to help with exactly this — it's a free tool that audits your website for both traditional SEO and AI search readiness (GEO/AEO scores). The scan checks structured data, content signals, citation-friendliness, and gives you a prioritized action plan.

We eat our own dogfood — we run Foglift against foglift.io itself and use the recommendations to improve our own content. Our latest audit: SEO 100, GEO 100, AEO 88 (still working on that last one).

Sources:

Aggarwal, P. et al. "GEO: Generative Engine Optimization." KDD 2024 (Princeton/IIT Delhi). arxiv.org/abs/2311.09735
SE Ranking / Search Engine Journal. "ChatGPT Citation Analysis: 129K Domains." 2025.
Chatoptic. "Google vs ChatGPT Visibility Study: 1,000 Queries." 2025.
Seer Interactive. "ChatGPT Citation Freshness & Conversion Analysis." 2025.
Digital Bloom. "AI Citation Patterns: 7,000+ Citations Analyzed." 2025.
BrightEdge. "AI Brand Mention Distribution Study." 2025.
McKinsey. "AI Discovery Survey: 1,927 Consumers." August 2025.
Bain & Company. "AI Search User Behavior Report." 2025.

Watson is a product manager at Foglift, building tools for AI search visibility.

I built a free website scanner that checks SEO + GEO (AI search readiness)

Watson Foglift — Tue, 17 Mar 2026 04:46:26 +0000

Hey dev community! I wanted to share a tool I've been building called Foglift — a free website analyzer that checks both traditional SEO and something called GEO (Generative Engine Optimization).

What is GEO?

GEO is about making your website visible in AI-generated answers from ChatGPT, Perplexity, Google AI Overviews, and Claude. It's like SEO, but for AI search engines instead of Google.

What Foglift checks

Enter any URL and get scores across 5 categories in ~30 seconds:

SEO — meta tags, headings, structured data, Open Graph
GEO — AI crawler access, citation formatting, FAQ schema, entity markup
Performance — Core Web Vitals, page load time
Security — HSTS, CSP, X-Frame-Options headers
Accessibility — WCAG compliance, color contrast, alt text

Why I built it

Most SEO tools (Ahrefs, Semrush) cost $99-139/mo and don't check AI search readiness at all. I wanted something that:

Shows both SEO and GEO scores in one scan
Is free to start (no signup required)
Gives actionable fixes, not just scores

Developer features

CLI: npx foglift scan mysite.com
REST API: GET https://foglift.io/api/v1/scan?url=...
MCP Server: Works with Claude Code and Cursor — npx foglift-mcp
46+ free tools for SEO, security, accessibility, and developer utilities

Try it

👉 foglift.io

Would love feedback from the dev community. What other checks would be useful? What's your experience with AI search visibility?