Unlocking AI SEO: Five Key Strategies for Creators

Kyle Scott discusses the evolving landscape of SEO in the context of AI advancements. He outlines the essential strategies for creators and marketers to adapt, including the use of structured data, intent-based phrases, and tagging across various content types. He also highlights the importance of optimizing for both digital and physical searches as AI technology continues to develop.

Takeaways

AI is transforming SEO, not eliminating it.

Structured data helps AI understand content better.

Natural language processing is key for future searches.

Tagging content improves visibility across platforms.

Implementing LLMS.txt can enhance AI crawling.

Physical search optimization is becoming crucial.

Links referenced in this episode:

• schema.org
• mintlify.com
• firecrawl.com

Companies mentioned in this episode:

• DraftKings
• Mintlify
• Firecrawl
• Meta

Episode Transcript

(00:00):
All right, I'm going to bedoing these short little voice memos
from time to time on apressing topic in digital media today.
I want you to start thinkingabout AI SEO. Most people think SEO
is dead thanks to AI, butthat's the wrong way of looking at
it. As someone who used tooversee $40 million in annual SEO

(00:22):
dependent affiliate revenue ina highly competitive space, here's
what I think every creator,marketer and business owner should
be doing right now to adapt.First, some context. While it's true
that AI is eating traditionalsearch results, someone still needs
to feed the AI. Gemini,ChatGPT and Perplexity all cite their

(00:45):
responses, especially ontransactional queries. I want to
call your attention to asearch for DraftKings promo code,
a highly valuable term foraffiliates in both chatgpt and Perplexity.
Both of those AI chatbots showyou the promo and bonus you can get
with DraftKings, but they citeleading affiliates like Action Network,

(01:08):
Sports Betting, Dime Rocky,Top Insider and the New York Post
and generally require you toclick those brands to learn more
and get the code, thus givingthem the affiliate attribution. So
how does one feed the hungryAI? Most current best practices apply
like linking, tagging andauthoritative content. That's cool.

(01:30):
Keep doing that. Let them eat.But based on hours of additional
research, here's what else youmust be doing for LLMs to like your
content. Number one, you needto output structured data. Use JSON
LD schema such as article,person or product on your content
and also use same as wherepossible. This helps AI LLMs quickly

(01:54):
contextualize and understandyour data, improving chances of landing
in snippets, AI overviews andchatbot results. If you have no idea
what the heck I'm talkingabout, go to schema.org and learn
more about the format thatsort of tags webpage and document
content to make it more easilyingestible not only for LLMs but

(02:16):
also existing search engines.Number two use intent based phrases
and questions. AI search ismultimodal in order of appearance.
That means chatbot voice andthen image and video search. People
ask natural language questionsin chats and through voice. The more
your content is framed tomatch these conversational queries,

(02:39):
the better it will do. Numberthree Tag everything. Most content
these days doesn't live onjust a website anymore. It's X posts,
YouTube videos, podcasts,newsletters on Beevin, Substack and
so much more. There will be agold rush for data licensing on everything

(03:01):
from influencer content tomedical records. The more everything
is tagged the better. Thatmeans using alt tags on images, transcripts
on podcasts, captions onvideos, and descriptions on images
and videos posted to socialmedia platforms like X and LinkedIn.
Hit the ad description whenyou upload an image to x or on LinkedIn.

(03:24):
This is basically alt text forsocial media and it helps the LLMs
and search engines bettercategorize the content you're putting
out. Number four Implement LLMLLMs txt Use a tool like Mintlify
or Firecrawl to generate anLLMs TXT file that LLMs can easily

(03:48):
crawl. While this isn'tindustry standard yet, many expect
AI bots to ingest these filesmuch the same way search engines
crawl. Robots Txt now again,if you have no idea what the heck
I'm talking about. Mostwebsites contain a file called robots
Txt and they containinstructions for for search engines
like Google on how they wouldlike to be crawled so that search

(04:11):
engine can ingest its data.Sometimes your robot may tell Google
you don't want to be crawled,other times and most times you tell
it you want to be crawled andhow to find your stuff. LLMs txt
is a proposed file format thatwould be more easily ingestible for
AI chatbots that are crawlingcontent. So to the extent you can

(04:32):
include one of these on yourcontent, there's no downside right
now. Number five Be Vision andPhysical World optimized if You've
played with ChatGPT's latestvideo chat feature, then you know
what I'm talking about. If youhaven't, you should try it out so
you can see what's coming andsoon. What's the use case? Well,
you look at something and thenyou ask questions about it. First

(04:56):
we'll do this with phone andsoon with glasses. For physical products
and in person experiences, usehigh contrast text and easily readable
fonts called optical characterrecognition, large 2D barcodes, QR
codes, NFC and RFID tags, ARmarkers, whatever. Use what you can

(05:17):
to help AI enabled devicesquickly identify items in the physical
world. Then make sure youconnect things like QR codes on boxes
to online assets and web pagesthat are properly tagged with schema,
which we just talked about afew minutes ago. Bringing everything
full circle here an example ofthis vision experience. Since it's

(05:38):
so hard I think for mostpeople to imagine today, even though
technology exists, might gosomething like this. Someone walks
down the sidewalk and looks ata pair of ski boots in a store window
while wearing the Meta RayBans. The glasses quickly scan the
QR code and present the userwith the product name, price and
sizes available in the store.Thanks to an integration with Shopify,

(06:02):
the store's website that theQR code points to has product and
same as schema, so the glassesare able to present the user with
similar products and reviews.All of this is possible because the
glasses easily identified theproduct they were looking at. This
is what's coming in Search.It's not just about online anymore.

(06:22):
The more we walk around withreal time AI cameras, whether through
our phones or soonubiquitously with glare, you need
to the AI needs to be able tolook and quantify that data quickly.
All right, so to recap, whatdo you need to do? 1. Structure your
data 2. Use natural languagephrasing 3. Tag everything. If there's

(06:43):
an option to add a descriptionor a Tag, do it. 4. Implement the
LLMs TXT file so AI chatbotscan better crawl your content and
then five implementations bethinking about physical search, especially
if you're a store owner or youdo something in the physical world.
All of this is just scratchingthe surface. It's very early days,

(07:04):
but I want you to know searchisn't dead. You just have to think
about it differently.