Copy the formatted transcript to paste into ChatGPT or Claude for analysis
At this point, you know how important it
is to rank in AI search. But with all
these AI visibility platforms and newly
self-proclaimed AI SEO consultants vying
for a slice of that sweet, sweet
marketing budget, it can be hard to know
what's real and what's snake oil. Well,
in this video, I'm going to empower you
to cut through all that noise and
actually do an AI search audit for
yourself for free, not including the
very small cost of these AI assistants.
It's a manual exercise and a slightly
tedious one. But just like Mr. Miyagi
taught Daniel Son wax on wax off before
the crane kick. I think before you go
spending money on an automated AI
visibility tracker, you should
understand how large language models
think, work, and what makes them
valuable lead generation channels. By
the end of this video, you'll know
exactly first how to conduct a
comprehensive audit that tracks both
citations and mentions across all major
AI platforms. And next, how to spot the
recurring sources that dominate AI
answers in your niche and get yourself
included in them. My name is Matt Canyon
and I help businesses improve their
brand visibility across organic
channels. And the organic channel in
vogue these days is almost always AI
search.
But before we dive into the audit
process, let's clarify what we're
actually trying to achieve here. In AI
search, there are really two ways to
win. First, you can get cited as a
source. That's when your URL appears in
the footnotes or references of an AI
search conversation. That's a good sign
because it means the AI found your
content valuable enough to reference.
But even better is getting your brand
mentioned by name in the actual answer.
And if you can get both a direct mention
and a citation, that's perfection. But
here's the challenge. AI visibility
audits are much trickier than
traditional SEO audits. With traditional
search, we have tons of data in Google
Search Console, reliable keyword
research tools, and predictable ranking
factors. AI search, on the other hand,
is incredibly volatile, and it's
evolving in real time. For one, AI
assistants are generative, meaning no
two answers will ever likely be the same
because the large language models under
the hood are generating the answer on
the fly. Secondly, factors like
personalization and a user search
history will affect how AI assistants
surface particular answers. As I
mentioned before, since open AI and
perplexity and anthropic are private
companies, it's not like we have access
to a query database so that we can see
what people are searching for. So AI
search is kind of a black box. But
thankfully, we can tease out insights by
prompting it and watching how it
collects sources as well as studying its
thinking process.
Okay, so for this audit, we'll be
focusing on at least one of the four
main AI platforms. Chad GPT, Google AI
overviews, Claude, or Perplexity. Now,
you're free to start with just one of
these, but if you tackle all four,
you're essentially covering 90% of all
conversational AI searches. Next, since
we don't have access to the actual
queries people are searching for, we
need to put ourselves in the customer's
shoes and understand what a customer
might search for. While traditional SEO
tends to focus a lot on the top of the
funnel with high volume, low competition
informational posts to bring in traffic,
for this exercise, we're squarely
focused on the middle and bottom of the
funnel. An example of a top offunnel
query might be why do I need an email
marketing platform? If you've written
content on the topic, you may get cited
as a source. But our goal is to get both
cited and mentioned by name, which
typically only happens with middle or
bottom of funnel queries. For example,
what are the best email marketing
platforms for small businesses? This
searcher has very clear intent. They
know they have a problem only an email
marketing platform can solve, and now
they're in the evaluation phase. I
recommend brainstorming two types of
queries. First is discovery queries with
no brand names. This is to test organic
appearance. And the second is
brandspecific queries to test sentiment
and accuracy. For discovery queries,
that might include things like what are
the best email marketing platforms for
small businesses? Which project
management tools integrate with Slack
and Google Workspace? What CRM software
works best for real estate agents under
$50 a month? And for brand specific
queries, you could do things like, how
does your brand compare to Mailchimp for
email marketing? What are the pros and
cons of your brand versus competitors?
And is your brand worth the price
compared to alternatives? In my
experience, it's highly beneficial to
pick the brains of your customer support
and sales teams for ideas. These are the
folks that are on the front lines,
actually speaking to customers,
understanding their pain points, and how
your product or service can solve them.
And if you need inspiration, I found AI
tools to be very helpful here. I've
added a prompt in the description of
this video that you can paste into your
favorite AI assistant that will study
your business and give you some ideas
for prompts for your company. It's up to
you how many prompts you'd like to test,
but I'd recommend at least five in each
category. Once you're happy with your
prompts, it's time to collect AI
responses systematically. Now, there are
certainly developer type folks who will
recommend using the APIs from these
companies to build custom applications
that will systematically query each of
these keywords. Now, if you feel
comfortable building or or even vibe
coding a script like this, go for it.
But if you're non-technical and you
don't want to mess with code, you can
achieve the same result in the browser.
For every query, I recommend opening
each platform in a new tab and making
sure you've enabled temporary mode on
chat GPT perplexity and claude and have
Google opened in an incognito browser.
There's still a lot of variability
between logged in and logged out chatgpt
chats, free or paid plans, not even
taking into account which model you're
using. All of these add so much
variability to AI responses. So, while
it's not perfect, we want to do our best
to isolate our variables and standardize
these experiments. Next, create a
spreadsheet with columns representing
each AI assistant and rows corresponding
to each query. Then, click the like
button on this video and subscribe for
more practical insights on increasing
your traffic, leads, and sales in the AI
SEO meta.
Anyway, once you're ready, just query
each assistant and copy and paste the
output into the corresponding cell of
your spreadsheet. Before moving on to
the next question, I recommend taking a
few seconds to click the thinking button
on chat GPT. It might be named something
differently depending on what AI
assistant you're using and study the
logic of how the AI assistant retrieved
its answers. Likewise, take a moment to
hover your mouse over each source
referenced in the answer. You'll
inevitably start seeing patterns of
sources referenced multiple times.
When you've completed your entire
spreadsheet, this is where the fun
begins. You can not only analyze these
answers manually, which is certainly a
useful and helpful exercise, but you can
feed this CSV back into a large language
model to get powerful insights at scale.
Here are the metrics I recommend
surfacing and the prompts for how to get
them. Make sure to attach your CSV to
each of these queries and check the
description of this video to easily copy
and paste each prompt. Number one,
mention volume. Now, mention volume
tracks how frequently your brand appears
across AI responses. This metric helps
you understand your overall AI
visibility. The prompt for measuring
mention volume, again, just grab that
from the description, will analyze the
CSV of AI responses and count how many
times each brand name appears across all
responses. It will also surface any
patterns in which certain types of
queries generate more mentions for
specific brands. This prompt should show
you all brands, but you can make it
specific if you just want to see yours.
Now, obviously, all your branded queries
will return mentions of your brand cuz
they're they're branded queries. So this
metric is most helpful if you isolate
your unbranded queries and have the AI
assistant analyze only those. Number
two, sentiment analysis. Now sentiment
analysis evaluates whether AI mentions
of your brand are positive, negative, or
neutral. This helps you understand not
just visibility but brand perception.
For this, you will want to put in both
branded and unbranded queries and
responses. The sentiment analysis prompt
will analyze the underlying sentiment of
each brand mention and categorize it as
positive, negative, or neutral, as well
as reveal the context behind it, whether
that's pricing, features, support, etc.
Number three is recurring source
analysis. Now, chances are this
experiment will reveal certain websites
or publications that the AI assistants
site over and over. These represent high
authority sources that you should either
target for coverage or compete against.
The prompt for surfacing recurring
sources will identify all sources or
URLs cited across AI responses and rank
them by their source domain, number of
citation, types of queries where cited
and competitive brands mentioned on each
source. It will also highlight
opportunities where your brand can get
featured on frequently cited sources or
just create competing content and
outrank them. Number four, we want to
figure out our competitive share of
voice. This is your brand's relative
visibility compared to key competitors
across all AI platforms. It provides
context for your performance and
identifies which competitors you need to
target in AI search. This prompt will
calculate competitive share of voice by
one identifying all brands mentioned,
two calculating each brand's total
mentions as a percentage of all brand
mentions, and three by showing share by
query type and AI platform. I know
that's a lot, but if you just copy and
paste the prompt with your CSV, I
promise it'll all make sense. It will
also highlight your biggest competitive
threats and opportunities to gain share.
Now, the sky's is the limit when it
comes to how you want to slice and dice
this data. These are just a few helpful
starting metrics, but you can also have
AI analyze your citation versus mention
ratio, query intent performance, and
honestly, whatever else you can think
of. I recommend running these analysis
prompts through at least two different
large language models like Claude and
ChatgPT, for example. And of course, be
sure to QA and verify the data before
presenting it to any stakeholders. Trust
but verify. That's the name of the game
when it comes to using AI for data
analysis.
And once you have these raw insights,
you can use AI to format them as a
stepbystep action plan. And yes, we have
a prompt for that in the description as
well. Just paste the action plan prompt
in along with your insights or in the
same chat as the previous prompts, and
it will create a prioritized 90-day
action plan with specific tactics to
improve your AI search performance.
You'll definitely want to edit this
before showing it to anyone else, but in
my experience, it's a really good start.
If you find that the large language
model is hallucinating answers or the
data seems to be too overwhelming to
provide useful responses, start by just
feeding it answers from one assistant at
a time. Now, once you've actually taken
action on your plan, I recommend waiting
about a month or so and rerunning this
entire process. Use the same prompts,
the same assistance, and track the same
metrics to see if your tasks are
actually making an impact. So, that
wasn't so bad, right? This manual audit
process might seem tedious, but it's the
foundation for understanding how AI
search really works. Once you've
mastered this systematic approach,
you'll have the knowledge to evaluate
any AI tracking tool that comes to
market. And more importantly, you'll
understand exactly what levers to pull
to improve your visibility. Whether
you're a soloreneur trying to get
mentioned alongside industry giants or
an established company looking to
maintain your market position in the AI
SEO era, this audit framework gives you
the data you need to make informed
decisions. Now, if you're ready to
actually dive deep into the tactics that
move the needle for AI search rankings,
check out this video next. We'll show
you the specific content strategies and
technical optimizations that get you
cited and mentioned across all major AI
platforms. Thanks for watching and happy
ranking.
54 minLunio