DEV Community: Rahul Bhadja

AI Visibility Is Mostly a Source Problem

Rahul Bhadja — Wed, 24 Jun 2026 11:15:24 +0000

Most AI visibility workflows start with prompt tracking.

You write a set of buyer-intent prompts, run them through ChatGPT, Gemini, Perplexity, and Google AI results, then record whether your brand appears.

That is useful.

But the prompt is only the entry point.

The better question is:

Why did the answer feel safe recommending someone else?

In B2B, that usually points to a source gap.

The basic loop

The loop I use is:

prompt -> competitor -> source -> gap -> action

The prompt shows what the buyer is asking.
The competitor shows who currently gets recommended.
The source shows what evidence the answer seems to trust.
The gap shows what is missing around your brand.
The action is what you fix next.

Without the last two steps, AI visibility becomes another scoreboard.

Useful, but not very operational.

What to track

Start with 10 buyer-intent prompts.

These should sound like real questions, not keyword fragments.

Examples:

best tools to track AI visibility for B2B SaaS
how do I know if ChatGPT recommends my competitors?
AI visibility platform for agencies
tools for monitoring brand mentions in AI answers
alternatives to [competitor] for AI search visibility

Pick 3 competitors buyers would realistically compare against you.

Then run the prompts across a few surfaces:

ChatGPT
Gemini
Perplexity
Google AI results where available

For each result, log:

prompt
surface
brand mentioned: yes/no
competitors mentioned
brand position: recommended / briefly mentioned / missing
sources or citations
category language used
first likely gap
next action

A spreadsheet is enough for the first pass.

You do not need a complex system to learn whether competitors have stronger public evidence.

Example source gaps

If a competitor keeps showing up and you do not, look at the evidence around them.

Common gaps:

A cited listicle includes competitors but not you.
A review site has competitor profiles but your profile is missing or weak.
Competitors have clearer comparison pages.
Your site does not use the category language buyers use in prompts.
Your docs explain features but not buying use cases.
Your homepage has claims but weak proof.
Trusted third-party sources describe the category without mentioning you.

The fix is rarely "publish 50 more blog posts."

The fix is usually more specific:

get listed on a source AI already cites
create a stronger use-case page
write a direct comparison page
add proof to the page that should answer the prompt
clarify your category wording
update docs, FAQs, or review profiles

A simple scoring table

If you want to keep this lightweight, use a table like this:

Prompt	Surface	Brand	Competitors	Sources	Gap	Action
best tools to track AI visibility for B2B SaaS	Perplexity	missing	Competitor A, Competitor B	listicle, review site	source excludes us	submit/update listing
AI visibility platform for agencies	Gemini	briefly mentioned	Competitor A	category article	agency use case weak	create agency page
alternatives to Competitor A	ChatGPT	missing	Competitor B	comparison pages	no direct comparison	publish comparison page

The point is not to build a perfect measurement system.

AI answers change.

The point is to find repeated evidence gaps and turn them into a backlog.

The useful output

Do not stop at:

We appeared in 2 out of 10 prompts.

That is only the score.

The useful output is:

Here are the first 5 things to fix.

Example:

Add the brand to the third-party list AI already cites.
Create a comparison page for the competitor that appears most often.
Rewrite the use-case page around the exact buyer question.
Add stronger proof to the homepage or category page.
Re-run the prompt set next week and check whether the source pattern changed.

That is where AI visibility becomes practical.

Why I care about this

I am building InfuseOS around this workflow:

track AI visibility
find competitor gaps
find source gaps
turn the findings into weekly Growth Actions

The goal is not to pretend AI answers are perfectly stable.

They are not.

The goal is to collect enough evidence to make better growth decisions.

If AI keeps recommending competitors, ask what makes them easier to recommend.

Usually the answer is sitting in the sources.

A Simple Manual AI Visibility Audit for B2B SaaS

Rahul Bhadja — Fri, 19 Jun 2026 17:45:54 +0000

If you work on B2B growth, SEO, or content, there is a new question worth adding to your workflow:

When buyers ask AI tools about our category, do we show up?

Most teams already know how to check Google rankings, organic traffic, and conversion pages.

That still matters.

But buyers are also asking ChatGPT, Gemini, Perplexity, and AI Overviews for recommendations before they visit websites or fill out forms.

This is a simple manual process I use to get a directional read on AI visibility.

It is not perfect. AI answers move around. The same prompt can produce different results over time. But as a first pass, it gives useful signals.

Step 1: Pick 10 buyer-intent prompts

Do not start with SEO keywords. Start with questions a buyer would actually ask.

For example:

best tools to track AI visibility for B2B SaaS
how do I know if ChatGPT recommends my competitors?
AI visibility platform for agencies
tools for tracking brand mentions in AI answers
best software for monitoring brand visibility in answer engines

Good prompts usually include:

the problem
the category
the buyer type
comparison or recommendation intent

Bad prompts usually look like keyword fragments.

Step 2: Pick 3 competitors

Choose competitors buyers would realistically compare against you.

Not only the companies you want to be compared with. Use the ones that already appear in sales calls, comparison searches, review sites, or category pages.

You want to track:

your brand
competitor 1
competitor 2
competitor 3

Step 3: Run the prompts across 2 to 4 surfaces

Start with:

ChatGPT
Gemini
Perplexity
Google AI Overviews, when available

For each prompt and surface, save the answer or screenshot. You do not need a big system for the first pass. A spreadsheet is enough.

Step 4: Track mentions

For every answer, mark:

brand mentioned: yes/no
competitors mentioned: names
brand position: recommended / briefly mentioned / missing

This gives you a directional view of whether AI systems connect your brand to the category.

The interesting part is not just whether you appear. It is who appears instead.

If competitors keep showing up and you do not, there is probably a public evidence gap.

Step 5: Track sources and citations

This is where the audit gets useful.

AI answers often rely on sources like:

listicles
comparison pages
review sites
documentation
partner pages
Reddit threads
trusted industry publications

If AI cites a source that mentions competitors but does not mention you, that source may be shaping the answer against you.

That is a concrete thing to fix.

Step 6: Convert findings into actions

A dashboard is useful, but the work is deciding what to do next.

Examples:

create a clearer comparison page
update a use-case page with the category language buyers use
get listed on a trusted source AI already cites
improve proof on your homepage
add a page for a prompt where competitors show up but you are missing
clarify positioning around a specific use case

The output should not be:

You appeared in 3 out of 10 prompts.

The output should be:

Here are the 5 things to fix first.

Why this matters

AI visibility is noisy, but it is not useless.

If buyers are using answer engines to shortlist tools, compare options, and understand categories, then B2B teams need to know:

are we mentioned?
who shows up instead?
what sources are trusted?
what should we fix next?

I am building InfuseOS around this workflow: track AI visibility, find competitor and source gaps, and turn them into weekly Growth Actions.

The goal is not another dashboard for the sake of it.

The goal is a clearer operating loop for B2B growth teams and agencies.

Check the prompts. Find the gaps. Fix the evidence. Repeat weekly.