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CASE STUDYAI citation growth via speed + structure

87 AI-Cited Pages in ~90 Days(without paid distribution)

Agenxus planned, wrote, and engineered an AEO-first publication designed for AI extraction—then backed it with elite performance fundamentals (Next.js + Vercel) to maximize crawl efficiency, content consumption, and citation eligibility.

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Site age
~3 months
from initial launch
Total URLs
283
Google Search Console snapshot
AI-cited pages
87
SEMrush AI Search tracking
Mobile performance
100
PageSpeed Insights
Next.js (React)Deployed on VercelSpeed-first architectureAEO-first content systemSchema + internal linking

The Goal

Build a new publication in a highly competitive niche and earn early visibility in both traditional search and AI-mediated discovery—where systems like ChatGPT and Google AI Overviews selectively cite sources they can crawl, parse, and trust.

What We Delivered (End-to-End)

  • Site build + engineering: Next.js (React) implementation deployed on Vercel with a performance-first approach and effectively no traditional hosting overhead.
  • Content creation: AEO-first editorial production (framework-driven outlines, comparison tables, direct-answer sections, and structured internal linking).
  • Technical AEO: Structured data strategy, extraction-friendly HTML patterns, crawl accessibility, and page templates built to be legible to LLMs.
  • Measurement: Tracking for AI citations + crawl/index coverage and continuous iteration based on observed performance.

Why Speed Was a Force Multiplier

In AI search, you don’t just “rank”—you get selected. Speed and stability reduce crawl friction, improve render reliability, and increase the odds that both search crawlers and AI systems can successfully retrieve and process your pages at scale.

Faster fetch + render
Less timeout risk, fewer partial parses, better extraction.
Lower bounce friction
Users and systems both “stick” longer when pages load instantly.
Scale-ready
Performance holds as content count grows—critical for new publishers.

Results Snapshot

According to SEMrush AI Search tracking, the publication reached 87 cited pages while the site had 283 total URLs indexed/discovered—an unusually high early citation-to-URL ratio for a ~3-month-old site in a competitive market.

Note: Citation tracking varies by tool and model. The takeaway isn’t the exact count—it’s the direction: strong early coverage is achievable when speed, structure, and trust signals are engineered from day one.
Evidence (Screenshots)
PageSpeed Insights mobile performance score screenshot
PageSpeed Insights: mobile performance at 100 (with strong accessibility/SEO).
Google Search Console screenshot showing total URLs
Google Search Console: total discovered/indexed URLs (placeholder—swap with your real screenshot).
SEMrush AI Search visibility cited pages screenshot
SEMrush AI Search: 87 cited pages (site-wide).
Tech Stack
  • Frontend: Next.js (React) + Tailwind CSS
  • Deployment: Vercel (fast global delivery)
  • Performance: Core Web Vitals-first build patterns
  • AEO: schema + extraction structure + internal linking system
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Want results like this?

We build and optimize sites end-to-end—from engineering and content creation to schema and AI citation readiness.

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AI engines don’t reward “good SEO.”They reward citability.

If you want citations, you need speed, structure, trust signals, and content built for extraction—not just keywords.

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