We've been deep in the world of Answer Engine Optimization, running the CiteMET playbook across our best content. The initial results were solid - we saw users engaging with our AI Share Buttons, and we knew we were successfully seeding our content into AI platforms. But with our team's background in AI, we saw this as just the first step.
We understood that for a Large Language Model (LLM), a single, quick interaction is a whisper. A true signal of authority, one that builds lasting memory, comes from a deeper conversation. We saw an opportunity to transform that initial whisper into a meaningful dialogue.
Introduction
You've built your SaaS with the speed of AI. You've launched. Now, you ask the same AI, "What is my product?" And it responds, "I can't access that page."
Sound familiar? This was the exact frustrating reality for GiveFeedback.co, a tool I co-founded to turn messy client feedback into clear tasks. We built it fast, we built it smart, and we even won a $100k global competition with it.
But for all its brilliance, GiveFeedback suffered from the same problem that plagues most modern, AI-generated web apps: it was invisible to the very AI it was built with.
This is a case study of how we took a high-performing, Client-Side Rendered (CSR) application, applied the C.M.E.T. Method, and achieved 100% AI and search engine visibility in under 24 hours using our own platform, cite-met.com.
The "Before": A Perfect App, An Invisible Website
Our initial audit of GiveFeedback.co revealed a site that was fantastic for human users, but a ghost to AI crawlers.
Phase One Audit: GiveFeedback.co (Before cite-met)
| Metric | Initial Score | Max Points |
|---|---|---|
| Static HTML Content | 0.0 | 5 |
| AEO Directives (llms.txt) | 0.0 | 2 |
| Structured Data (JSON-LD) | 0.0 | 2 |
| SEO Meta Tags | 2.0 | 3 |
| Total C.M.E.T. Score | 4.0 | 12 |
| Visibility Grade | F | - |
The biggest culprit was "Static HTML Content." As a modern React application, GiveFeedback relied entirely on JavaScript to render its content. To AI, it was just
<div id="root"></div>Zero points for static content. Zero points for AEO directives. Zero points for structured data. We had a visibility problem, and it was foundational.
The C.M.E.T. Transformation: One-Click Deployment
Our goal was simple: fix the "Blank Page Problem" and give AI crawlers all the signals they needed to understand, trust, and cite GiveFeedback.
We deployed GiveFeedback.co to cite-met.com. The process involved:
1. Connecting GitHub: Linking our GiveFeedback repository.
2. Automated SSG Conversion: cite-met's engine automatically converted the entire CSR app into a blazing-fast Static Site Generated (SSG) output. This immediately fixed the "Static HTML Content" issue.
3. AEO Directive Injection: cite-met auto-generated and injected a dynamic
llms.txtsitemap.xmlrobots.txt4. Structured Data Enhancements: We added
FAQPageSoftwareApplicationThis entire process, from connecting the repository to a fully deployed and optimized site, took less than 24 hours.
The "After": 100% Visibility & Real-Time Citations
The impact was immediate and measurable.
Phase Impact Audit: GiveFeedback.co (After cite-met)
| Metric | Score After cite-met | Max Points |
|---|---|---|
| Static HTML Content | 5.0 | 5 |
| AEO Directives (llms.txt) | 2.0 | 2 |
| Structured Data (JSON-LD) | 2.0 | 2 |
| SEO Meta Tags | 3.0 | 3 |
| Total C.M.E.T. Score | 12.0 | 12 |
| Visibility Grade | A+ | - |
GiveFeedback.co was now 100% visible and citable.
But the real proof came from how AI models began to interact with the site. Our analytics dashboard started showing visits from
ChatGPT-UserGooglebotClaudeBotAI Models React: The Difference Was Profound
We immediately started testing the new deployment with leading AI models. The results were night and day.
ChatGPT: When asked "What is GiveFeedback.co?", ChatGPT now correctly identifies it as a feedback management tool with accurate feature descriptions, citing our site directly. Before cite-met, it would respond with "I can't access this page."
Perplexity: Perplexity now includes GiveFeedback in comparisons with similar tools, pulling accurate pricing and feature data from our newly visible site. It cites us alongside established competitors.
Claude: Claude can now access our documentation and provide implementation guidance to users asking how to integrate feedback tools into their workflow.
Analytics Impact in the First Week:
- 300% increase in organic AI-driven traffic
- First citations appeared within 48 hours
- AI crawler visits increased from 0 to 15+ daily
- Direct referrals from AI-generated responses started appearing in our acquisition funnel
The most striking change? Users began telling us they "found us through ChatGPT" or "read about us in a Perplexity summary." This was traffic we literally could not access before.
Key Takeaways & What This Means for You
If you've vibecoded your SaaS with AI, there's a good chance it's invisible to that same AI. Here's what we learned:
1. The Blank Page Problem is real. CSR apps are ghosts to crawlers. If you're using React, Vue, or any JavaScript-heavy framework without SSG, you're invisible.
2. AI doesn't guess—it skips. If your site doesn't provide structured, machine-readable data, AI models won't hallucinate your features. They'll just cite your competitor instead.
3. The transformation is fast. From F to A+ in under 24 hours. The tooling exists. The methodology works. You don't need to rebuild from scratch.
4. Dogfooding matters. We built cite-met because we had this exact problem with GiveFeedback. Using our own platform proved its value and gave us the credibility to recommend it to others.
The bottom line: You can't win in the age of AI if AI can't see you. GiveFeedback.co went from invisible to cited in less than a day. Your site can too.
👉 Run Your Free Visibility Scan – See your score in 60 seconds.
👉 Deploy Your Site with cite-met – Go from F to A+ like we did.