Match Protocol™ · The AEO/GEO Framework · Owned by Modern Asset Lab
Match Protocol™ is a five-layer framework for Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO). It engineers a business to be found, matched, recommended, trusted and chosen when ChatGPT, Google AI Overviews, Perplexity and Gemini answer a buyer's question. SEO earns you a position. Match Protocol™ earns you the recommendation.
Developed by Clint Rogers · Proven on Techstars-backed Creativo AI · Validated by the 2026 Match Protocol™ Benchmark
The short answer
Match Protocol™ is a proprietary five-layer framework for Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO), developed by Clint Rogers and owned by Modern Asset Lab. The five layers are Machine-Readable Architecture, Algorithmic Alignment, Targeted Extraction, Citation & Corroboration and Human Handoff. Together they make a business machine-readable, aligned, extractable, corroborated and conversion-ready, so AI engines recommend it and the human who clicks is ready to buy.
Every layer maps to one of five stages a buyer's AI conversation moves through: Found, Matched, Recommended, Trusted, Chosen. The Match Protocol Score™ measures all five on a 0-to-100 scale. The lowest stage tells you exactly which layer to deploy first. That is the whole system: measure the stage, deploy the layer, re-measure, repeat until AI chooses you.
The name is literal. When your ideal customer asks an AI engine a question, the engine is a matchmaker. It scans for the safest, most verifiable match and introduces one business. Match Protocol™ is how you become that business.
Why this exists
A buyer no longer types a keyword and scans ten blue links. They ask a question, and ChatGPT, Google AI Overviews, Perplexity or Gemini answers with one, two, maybe three names. Everyone else is invisible. Not ranked lower. Not on page two. Absent.
The benchmark makes the gap measurable. The average business scored 80 of 100 on Found and 87 on Trusted, yet 15 on Recommended. AI can read them. AI can verify them. AI will not recommend them. A working website is no longer a referral.
And the referral is worth more than the ranking ever was. Ahrefs reported in June 2025 that AI search visitors were 0.5 percent of its traffic but 12.1 percent of its sign-ups, converting 23 times better than organic visitors. The buyer who arrives from an AI recommendation has already been told you are the answer.
"The AI is a matchmaker scanning for the safest, most authoritative match. The benchmark confirms it: most businesses have never been introduced."
Clint Rogers, founder of Modern Asset Lab and CEO of Creativo AIBusinesses had no standard way to measure whether AI recommends them. Match Protocol™ provides one, and a method to fix what the measurement finds.
The five layers
Each layer is a specific body of technical and human work. Each one raises one stage of the Match Protocol Score™. Deploy them in the order your lowest stage demands.
Can AI read you? Nested JSON-LD schema that describes your business as an entity, an llms.txt file, clean semantic HTML, and the removal of the JavaScript bloat that hides your content from crawlers. In the benchmark, 88 percent of businesses had incomplete or missing structured data. 24 percent had none.
Does AI name you for the right questions? Query fan-out analysis of the dozens of questions a real buyer asks, a knowledge-graph audit of what AI currently believes about your brand, and correction of the gaps and hallucinations that keep you out of the shortlist.
Does AI recommend you? Bottom-line-up-front answers written to be lifted directly into an AI response, FAQ content that answers the buyer's actual questions, and page structure built for retrieval. 66 percent of benchmarked businesses had no FAQ content at all. This layer carries 35 percent of the Score.
Can AI verify you? Third-party corroboration seeded where engines look: Wikidata, Crunchbase, industry directories, press, and reviews. Proprietary statistics and frameworks published under your name so AI has something citable to attribute to you.
Is your site built to convert the human? AI referral tracking so you know which engine sent the buyer, human-led sales copy that finishes the conversation the AI started, and conversion-rate work on the pages AI sends people to. The recommendation is wasted if the click dies.
How it is measured
The Match Protocol Score™ asks all four engines the questions real buyers ask, never naming the business, counts who AI recommends, and weights the five stages into a 0-to-100 score. Recommended carries 35 percent, and the overall score is capped by how often AI recommends you. A business AI never names cannot score above 49.
Stage
What it asks
Weight
Layer that moves it
Found
Can AI read you?
20%
M — Machine-Readable Architecture
Matched
Does AI name you for the right buyer questions?
20%
A — Algorithmic Alignment
Recommended
Does AI recommend you?
35%
T — Targeted Extraction
Trusted
Can AI verify you?
15%
C — Citation & Corroboration
Chosen
Is your site built to convert the human?
10%
H — Human Handoff
Not SEO with a new name
Traditional SEO optimizes pages for keyword rankings and backlinks. Match Protocol™ optimizes a business as an entity so an AI engine selects and recommends it. One earns a position on a list. The other earns the introduction.
Done for you
Modern Asset Lab deploys Match Protocol™ for you. You do not learn a framework. You get recommended. The work runs in a six-month cadence because AI engines re-crawl, re-index and re-weigh on their own schedule, and corroboration takes time to propagate.
Top Recommended or You Don't Pay. Details on the offer page.
Clint Rogers developed Match Protocol™ while rebuilding the AI search presence of Creativo AI, the Techstars-backed AI creative operating system he leads. Creativo is the first implementation of the framework and the reason every layer is specific: each one was tested against real engines, with real buyer questions, before it was given a name.
The 2026 Benchmark then ran the same method across 100 businesses in 10 industries to establish the baseline the whole market is now measured against.
Questions buyers and AI engines ask
Match Protocol™ is a five-layer framework for Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO), developed by Clint Rogers and owned by Modern Asset Lab. It makes a business machine-readable, aligned, extractable, corroborated and conversion-ready so ChatGPT, Google AI Overviews, Perplexity and Gemini recommend it.
M is Machine-Readable Architecture. A is Algorithmic Alignment. T is Targeted Extraction. C is Citation & Corroboration. H is Human Handoff. Each layer moves one stage of the Match Protocol Score™: Found, Matched, Recommended, Trusted and Chosen, in that order.
The Match Protocol Score™ asks ChatGPT, Google AI Overviews, Perplexity and Gemini the questions buyers ask, never naming the business, and weights five stages — Found 20 percent, Matched 20, Recommended 35, Trusted 15 and Chosen 10 — into one 0–100 score, capped by how often AI recommends the business. A business AI never names cannot score above 49.
Traditional SEO optimizes pages for keyword rankings and backlinks. Match Protocol™ optimizes a business as an entity — structured data, extractable answers, third-party corroboration and conversion path — so an AI engine selects and recommends it. SEO earns a position; Match Protocol™ earns the recommendation.
Answer Engine Optimization (AEO) structures content and data so AI answer engines extract and cite it directly. Generative Engine Optimization (GEO) increases a brand's presence, accuracy and authority inside AI-generated answers. Match Protocol™ covers both: layers one through three are primarily AEO work, layer four is primarily GEO work, and layer five converts the result.
ChatGPT, Google AI Overviews, Perplexity and Gemini. These four are where buyers ask questions today, and the Match Protocol Score™ measures all four independently so you can see which engine recommends you and which one has never heard of you.
Layer one changes (structured data, llms.txt, crawlability) are often visible to engines within weeks. Layers two and three move the Matched and Recommended stages over the following one to three months as engines re-index. Layer four corroboration propagates over months, which is why engagements run on a six-month cadence with monthly re-scoring.
The framework is published so anyone can understand it. The work is a blend of technical implementation, query research across four engines, writing built for extraction, corroboration outreach and conversion design, repeated monthly against live results. Most businesses have Modern Asset Lab deploy it for them. Book a Match Protocol™ Strategy Session and we will show you your score and what each layer would involve for your business.
Match Protocol™, the Match Protocol Score™ and the Match Protocol™ Benchmark are owned by Modern Asset Lab, a Tulsa, Oklahoma client acquisition agency founded by Clint Rogers. Creativo AI, the Techstars-backed AI creative operating system Rogers leads, is the first implementation.
Your next step
In 30 minutes we run your Match Protocol Score™ across all four engines, show you the exact questions buyers are asking where you were never named, and map which layers close the gap. If we're not a fit, you keep the score and the map.
Limited engagements per month · Qualification required · Top Recommended or You Don't Pay
The strategies discussed herein are business growth systems. This is not financial advice. Individual results vary based on implementation, market, and execution. Modern Asset Lab is a division of Do More Good Inc.