AI visibility tools for a small business: which one is for what

Seven pricing tabs open and no answer in any of them. The plans run from twenty-nine dollars to five hundred a month, every one promises the same thing in the same words, and none explains what actually changes between them beyond how many prompts you get to track. The question worth asking before you read a single feature grid is duller than any of those comparisons, and it decides most of the spend: do you need a snapshot or a film?

This comparison is written for someone who cannot sign a three-figure monthly subscription without knowing exactly what it buys. It includes Inspeccia, which is ours, and it also says where you should not use it.

The first fork: snapshot or film

Two different products are sold under one name. One answers am I there? and takes a single run: you ask the model the questions your customer would ask, you record whether it names you, who it names instead, and which sources it cited. The other answers am I moving? and needs that run repeated daily for months before the line means anything.

The second costs five to twenty times more, and fairly so — running hundreds of prompts a day against eight engines has real infrastructure behind it. Price is not the problem. The problem is that continuous monitoring only pays for itself when somebody acts on the week's delta: ships a page, fights for a slot on someone else's list, corrects a listing, emails a client. If the dashboard gets opened in month one and never again, you bought a chart.

With that in mind, the table reads differently.

The comparison

Prices verified on July 28, 2026 against each vendor's own pricing page. They change often and vary by currency and annual billing, so open the link before you pay. Where a company does not publish a retrievable figure, we say so instead of inventing one.

What each one is genuinely better at

Profound runs the most ambitious citation index in the category, and that is a real difference rather than a marketing one: looking at which domains feed answers at scale surfaces patterns no single run will show you. If your job involves explaining to a board why a competitor appears and you do not, that material earns its price.

Peec AI publishes the most rigorous research anyone in this space puts out. The most useful piece this year analyzed close to 200,000 responses across eight engines and more than 5.7 million data points, and measured something almost nobody measures: how much your visibility changes depending on where you sit inside somebody else's list. That finding comes back later in this piece, because it changes what is worth doing.

Otterly is the cheapest door into continuous monitoring, and for a small brand that matters more than sophistication. AthenaHQ and Scrunch are built for a different conversation — procurement committees, several teams, security requirements, annual contracts. That is an audience, not a flaw.

And if you already pay for Semrush or Ahrefs, the arithmetic changes completely. The AI module bundled into what you already own is usually enough to start with, and adding a dedicated tool on top is a decision worth postponing until you have a question the suite cannot answer. We go through that in more detail in the Semrush comparison and the Ahrefs comparison.

Where Inspeccia sits, and where it does not

Inspeccia is a one-off report. We ask a model, with web search live, the questions a customer in your category would ask, and hand back what it said: whether it names you, who it names instead, the words it uses to describe you, and — the part people actually use — which domains it cited as sources. You pay once or you do not pay: the base analysis is free and the full plan is $29, one time.

That makes it good for one case and wrong for another. It is the run you do before deciding whether you need monitoring, or when you want a snapshot without committing to twelve months of billing. It is also what you reach for when somebody tells you AI is saying something odd about your company and you want to see it yourself.

If what you need is an alert when your brand drops out of an answer on a Thursday, Inspeccia will not help. There is no daily dashboard and no historical series, and we are not going to pretend a single run replaces six months of tracking. Otterly, Peec and Profound do that, and choosing among them comes down to how many brands and how many markets you have to cover.

The five questions that decide the purchase

Feature grids do not help, because every tool has the same features written differently. These five questions do separate them:

1. Snapshot or tracking? If nobody will open the dashboard in month two, do not buy the dashboard.
2. How many brands and how many markets? Almost all pricing in this category is organized around that: projects, countries, prompts. One brand in one country is the cheap scenario; five clients across three countries pushes you up a tier in every tool at once.
3. Is knowing whether you are named enough? Knowing you appear 18% of the time tells you nothing to do on Monday. Knowing the model cited Trustpilot, a directory, and none of your own pages does. In our audits each mentioned brand carries 2.65 sources on average, and in 26.9% of cases the model does not cite the brand's own site at all.
4. Are you reporting to a client? Then you need a reproducible method more than a score: which questions, which model, which date, which sources. An index you cannot reconstruct is a promise, and promises get audited in the third meeting. If you work with clients, the agency guide goes into what the deliverable should contain.
5. How much movement can you tolerate in the number? Hardly anyone asks this one, and it matters most.

Whatever number you buy is going to move

There is a comfortable belief in this market: that your AI visibility percentage is a property of your brand, like organic traffic, and the tool simply reads it off. It does not survive contact with the data.

SE Ranking ran the same 10,000 keywords three times on the same day in Google AI Mode. Average overlap of exact URLs across the three runs was 9.2%, and 2,006 keywords — one in five — shared not a single URL. At the domain level it improves barely: 14.7%.

Our own database shows the same thing, and we publish it even though it does not flatter us. Out of 2,324 audits across 2,021 unique domains, 167 domains were audited two or more times. Among the 51 that were visible at least once, 56.9% returned a different result on the repeat run, with an average swing of 30.8 points of mention rate. Counted across all 167 the swing drops to 9.4 points, but only because most were invisible in every run, and the stability of zero is not good news.

Our method has limits worth stating: a single LLM provider, a cap of twelve source domains stored per analysis, and categories declared by the user. With those caveats, the practical conclusion holds. If two tools give you different numbers, the likeliest explanation is that both are measuring a moving system correctly. Comparing one method against itself over time is useful. Comparing one tool's number against another's is not.

It is also why Semrush, across an index of 126 million AI search prompts, found that 45% of marketing leaders cannot accurately measure their brand's visibility in AI answers and only 9% have tools to track every metric they care about. The shortage is not of tools. What is being measured refuses to hold still.

If you want to build your own method before paying for anything, the procedure is in the guide to measuring your AI visibility, and the traffic that does reach your site is measured separately, in Analytics 4.

Why you are reading a list

This article is a numbered comparison, and that is not an accident or laziness about format. It is the format AI cites more than any other, and three independent measurements point the same way.

Ahrefs analyzed 26,283 URLs cited by ChatGPT across 750 prompts covering software, products and agencies: 43.8% of cited page types were "best X" lists. Of the 1,100 lists whose dates it could read, 79.1% had been updated in 2025. Evertune, looking at more than 40,000 URLs ChatGPT cited heavily over sixty days across nearly fifty product categories, found that 50% of citations are listicles, and 58% of those are ranked lists.

Peec AI measured the part that actually affects your budget: being on the list is not the whole job, position inside it matters. Across nearly 200,000 responses from eight engines, sitting first in a third-party list was worth +16.5 percentage points of visibility in B2B SaaS and +13.4 in emerging martech. In US finance the rank ordering proved less predictable, which they say themselves.

For a small business the consequence is uncomfortable, because it redistributes the work. A good share of the effort you put into your own website returns less than getting onto — and climbing — the third-party lists AI already cites in your category: the trade blog's roundup, the association's ranking, the forum thread, the local paper's piece. Finding out which lists those are is, in practice, the most actionable part of any measurement. And it is a question a single run answers, not twelve months of subscription.

Frequently asked questions