How to Track Your Brand Visibility in AI Search (Free Method)

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.