TTT framework
The framework we use to help clients win YouTube citations in AI search.
đ Hey, Iâm George Chasiotis. Welcome to GrowthWaves, your weekly dose of B2B growth insightsâfeaturing powerful case studies, emerging trends, and unconventional strategies you wonât find anywhere else.
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We recently ran a live, 2-day intensive AEO cohort.
People loved it, and since the next live cohort isnât until October, we decided to make the course available on demand.
So, if you want to understand how AI search works in 2026 and what you can do to improve your visibility across AI search engines, you can now go through the same material at your own pace.
Youâll get access to the recordings, resources, and frameworks from the live cohort.
The course is $499 and already has a 5-star rating from people who joined live.
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YouTube is working well for some of our clients right now, and I keep seeing the same patterns in what works and what does not.
The channel is becoming more important for AI search.
AI search tracking tool, OtterlyAI, analyzed over 100 million AI citations and found YouTube accounts for 31.8% of all social media citations.
So the opportunity is realâŚ
But most companies approach YouTube without a framework for how these search engines actually process video content.
Here is a simple one we use at Minuttia.
TTT: Topic, Title, Transcript
We call it: TTT framework
The framework has three parts. Each one maps to how AI platforms evaluate and cite video content.
Topic
The video has to cover something relevant to the business and its business model.
That includes commercially focused topics most companies avoid because they require mentioning competitors.
You do not have to create a âtop 10 toolsâ listicle to go after a commercial term.
There are ways to cover that topic without the self-promotional format.
Why this matters: OtterlyAIâs study found that 94% of AI citations go to long-form videos, not Shorts. The cited videos are explainers, walkthroughs, tutorials, and case studies. If your topic selection produces those formats, you are aligned with what gets cited.
Letâs move on to the next one.
Title
The title is one of the first things AI engines read to decide whether a video is relevant.
That does not mean stuffing your title with keywords.
It means making it obvious what the video covers.
When the search engine crawlers discover your video, it should be very easy and straightforward for them to understand what itâs about.
(Obviously, the same goes for humans.)
Thus, my suggestion is to forget about creativity for a moment and pick a title that may be boring but is super representative of what the video is about.
Hereâs a quick example to illustrate the importance of the video title in getting visibility in AI search (even though I know some of you wonât agree with this approach):
The term Iâm using here is âbest aeo agencies,â which is an important term for my agency, Minuttia.
Our agencyâs Managing Director created a short video to cover that term, which (no surprise) has visibility on the first page of search results.
As you can see, the title is super specific and exactly matches the target term.
Obviously, the title isnât the only reason the video was picked up in this example, but it certainly is one of them.
One more to go.
Transcript
This is the content itself.
And probably the part that matters most.
LLMs consume the transcript. They do not watch the video!
What you actually say, and how naturally your brand comes up or how well-constructed your answer is, is what these engines read and take into account.
OtterlyAIâs correlation data from the above study supports this.
Views, likes, and subscribers show near-zero correlation with citation frequency (r = -0.03).
The popularity signals YouTube rewards internally are irrelevant to how AI decides what to cite.
What correlates with repeated citations is structure:
description length (r = 0.31)
hashtag presence (r = 0.20)
and timestamp chapters that make individual segments citable.
This is why brand mentions inside a video carry so much weight for AI visibility. The transcript is the raw material LLMs work with. If your brand appears naturally in an answer to a buyerâs question, AI engines are more likely to surface that video as a cited source.
AI search engines form their perception of your brand from the content they retrieve. Video transcripts are part of that content layer now.
Authorâs Note: You can learn more about all these sources of influence in my note on Perception Deviation.
None of the three works alone
You need all three.
Pick the right topic, but write a vague title, and the video might be skipped. Nail the title over a thin transcript, and the engine ignores it.
The overlap is where citation happens.
Timestamps as citation multipliers
OtterlyAI found that 78% of timestamped videos were cited multiple times, often across two to five different chapters. Each chapter is its own citable unit.
Think of timestamps as heading structure for video. An H2 on a web page lets search engines cite a specific section. A YouTube chapter does the same thing for a specific segment.
One well-structured video with clear chapters can earn more AI citations than five unstructured ones covering the same ground.
(Only Google currently uses timestamped citations. Perplexity, ChatGPT, and the rest link to the full video. But inside AI Overviews and AI Mode, chapters are a real advantage.)
Final Thoughts
YouTube visibility in AI is not about going viral. The data makes that clear.
Popularity metrics show no meaningful correlation with how often a video gets cited.
What matters is whether the video answers a question well enough that an AI engine considers it a reliable source.
Topic, Title, Transcript. Get all three right, and citations may follow.
Thank you for reading todayâs note, and see you again next week.
Research Disclaimers and Limitations
GrowthWaves and its author are not sponsored by or compensated by any company mentioned in this note. This is independent editorial analysis and does not constitute investment, financial, or legal advice. The author may have relationships with, work with, or hold equity in companies referenced; however, no content in this piece was influenced, commissioned, or incentivized by any such relationship. AI tools were used as a research assistant in the preparation of this piece. All claims are sourced and linked throughout.
Sources
OtterlyAI, âThe YouTube Citation Study 2026â
GrowthWaves, âPerception Deviation: The most important metric youâre not trackingâ
GrowthWaves, âSelf-promotional listicles are due for a correctionâ