The New “Leak” in the Funnel
As a consultant who has specialized in B2B SaaS and technical SEO for over a decade, I’ve seen the industry pivot many times. But nothing compares to the shift we are witnessing now.
As a consultant, the most frustrating conversation I have with B2B SaaS clients right now goes like this: “Burim, our technical health score is 98%. We rank #1 for the head term. But when I ask ChatGPT or Perplexity about the best solution in our niche, it cites a Reddit thread and our competitor—not us.”
This is the new reality. You can win the Ranking game (traditional SEO) and still lose the Citation game (Generative Engine Optimization).
I realized about a year ago that my standard audit checklist—crawl depth, Core Web Vitals, backlink profile—was necessary, but incomplete. It ensured the site was healthy, but it didn’t ensure the content was trustworthy to a Large Language Model (LLM).
This realization forced me to build my own proprietary SEO audit framework—a methodology designed not just for search engines, but for the Large Language Models (LLMs) that now dictate search success. This framework is what now drives every single client engagement I take on.
I’m sharing the structure of my framework below. And because I believe in speed and scale, I’ll also show you the single piece of technology I rely on to execute it efficiently.
1. The Evolution: Adding the “Trust Layer”
To be clear, the traditional SEO audit is still necessary. You must check for technical hygiene: site speed, crawl budget, broken internal links, and a strong domain foundation. This is the first phase of any engagement.
The value isn’t just in finding broken links anymore. The value is in finding and fixing the invisible, deep-level structural issues that are blocking your content from being seen as a credible, citable source of truth.
Here is what a traditional audit fails to measure:
- Trust Signals for AI: Does your content structurally prove its authority? AI models are voracious, but they are also skeptical. They are trained to heavily prioritize what Google calls helpful, reliable, people-first content. If you don’t signal your authority via verifiable, structural data points, you will be ignored.
- Extraction Readiness: Is your content formatted so that an LLM can easily pluck out the definitive answer and use it in a generative summary? If your answer is buried in long paragraphs, the LLM will move on to a competitor.
I didn’t stop doing traditional technical audits. You can’t build a house without a foundation. But I have added a second, non-negotiable layer to every engagement.
I call it the 3-Pillar Generative Framework.
It’s not magic. It is simply a rigorous, code-level verification of the signals that LLMs and Answer Engines use to determine if a piece of content is a “fact” or just an “opinion.”
Here is the exact logic I use to close the gap between ranking and being cited.
2. My 3-Pillar Consulting Framework
To solve this modern problem, I developed a 3-Pillar framework that I now deploy with all my clients. All three pillars must be checked simultaneously for a client’s content to achieve genuine Generative Search Wins.
Pillar 1: Entity-Level E-E-A-T (The Code Check)
We often talk about E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) as a vague, philosophical concept. In my audits, I treat it as a technical requirement.
- The Check: I stop looking at just the bio photo and start looking at the schema. Is the
Authorschema present? Does it use thesameAsproperty to link to verifiable third-party profiles (LinkedIn, Crunchbase)? - The Goal: To ensure the “Entity” (the author and the brand) is explicitly defined in the code, removing ambiguity for the bot.
Pillar 2: Generative Engine Optimization (GEO) (The Data Check)
Generative Engine Optimization GEO is the strategic practice of optimizing your content to be consumed and cited by the LLMs themselves. This is about data integrity and originality.
Key Checks: Is your data formatted to be verifiably original (e.g., “According to our Q3 report…”)? Is your content fact-dense rather than just keyword-dense? Do you provide clear, quantitative proof points that an AI can use in a citation block?
- The Check: I audit the content for “Verifiable Data Points.” Does the page make a claim (“We increase ROI”) without a number? Or does it provide a specific percentage (“40% increase”)?
- The Goal: To increase the “Data Density” of the page, making it statistically more probable that an LLM will latch onto it as a source of truth.
Pillar 3: Answer Engine Optimization (AEO) (The Structure Check)
Answer Engine Optimization AEO is the technical discipline of structuring content for easy extraction by generative models. AEO is about reducing friction. Can the bot extract the answer without reading the whole page? It is the tactical counterpart to GEO.
Key Checks: Are your headings phrased as questions? Are tables formatted correctly with <thead> and <tbody> tags? Do you use technical structured data like FAQPage and review the requirements for features like Google’s official gallery of supported structured data to ensure eligibility for rich results? This proves that your content is immediately usable by the Answer Engine.
- The Check: I look at the Information Architecture. Are
<table>tags used for data comparisons (easy to parse) or just<div>tags (hard to parse)? Are H2 headings phrased as questions? - The Goal: To structure the content so it can be essentially “dragged and dropped” into an AI Overview or Featured Snippet.
3. The Technology Partner
This framework is complex. It requires checking dozens of highly technical, rule-based signals across hundreds of pages. Doing this manually for every client would be impossible; the time investment alone would make my services cost-prohibitive.
To execute this complex framework at speed and scale, I rely on a dedicated, rules-based technology: The SEO Grow GEO Audit Tool.
This tool is the indispensable technology partner that underpins my consulting methodology.
It is the only way to accurately measure the granular, code-level GEO signals that traditional tools miss. It does not use a public LLM to “guess” your score. Instead, it is hard-coded with the exact proprietary logic of this 3-Pillar framework, programmatically checking for data density, schema integrity, and the structural signals necessary to satisfy E-E-A-T and LLM citability.
This is the distinction that matters: while I provide the custom strategy, the SEO Grow tool provides the objective, verifiable data, allowing me to deliver high-impact results faster than ever before.
The future of high-value SEO consulting rests on the ability to move clients from being participants in the old ranking game to becoming citable authorities in the new generative search landscape.
If you are a prospective client looking for a full-service custom strategy, deep expertise, and a guaranteed roadmap to Generative Search Wins, then contact me for a consultation.
If you want the exact technology I use to run the audit yourself, and are ready to stop guessing and start running a rules-based audit today, then start your free audit here.