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You're Probably Overspending on AI Visibility. Here's Why $20/Month Might Be Enough.

There are now fifteen-plus tools promising to show you how AI talks about your brand. Prices range from $20 to over $1,000 a month. The technology underneath is almost identical. So what exactly are you paying for?

Twelve months ago, "AI visibility" was barely a category. A handful of startups were building dashboards to track whether ChatGPT and its competitors mentioned your brand. Most marketers hadn't thought about the question seriously.

By March 2026, the market had exploded. Ahrefs launched Brand Radar. Semrush bundled AI tracking into their suite. SE Ranking spun up a separate product for it. On the startup side — Otterly, Peec, LLM Pulse, AI Peekaboo, Beamtrace, and a growing list of others — all shipping features at the pace of a category that smells like money.

The result is a pricing landscape that makes no intuitive sense. Entry points range from $20 to $355 a month. Full-featured setups can run past $1,000. And nearly every landing page makes the same promises about "understanding how AI sees your brand."

Here's the thing nobody in the category wants to say out loud: the core technology is identical.

The API call isn't the product

Every AI visibility tool does the same thing at the technical layer. It sends prompts to LLM APIs — ChatGPT, Gemini, Perplexity, whoever — parses the responses, checks whether your brand got mentioned, and plots the trend over time. That's it. That's the engine.

This isn't a criticism. The value these tools provide is real: structured, repeated measurement that turns a vague anxiety ("does AI know we exist?") into data you can act on. But it means the differentiation between tools isn't in the technology — it's in coverage breadth, tracking frequency, analytics depth, and UX.

And that distinction matters for how you spend.

What you're actually paying for across the price range

At the bottom of the range, a tool like Beamtrace gives you entry-level tracking for $20 a month. You get ten prompts, ChatGPT tracking (with other platforms on the way), a visibility score, automatic competitor detection, and tracking every three days. It's backed by the team behind Elfsight — thirteen years of SaaS, over three million users — so it's not a weekend project that might disappear.

At the top of the range, you're looking at enterprise-grade platforms with hundreds or thousands of prompts, daily tracking across six AI platforms, agency reporting, and compliance features. Ahrefs Brand Radar with full platform coverage, for instance, runs north of $800 a month on top of a base Ahrefs subscription.

The question is whether the gap between those two extremes is proportional to the price difference.

The 80% argument

ChatGPT holds roughly 80% of the AI search market right now. That single data point reshapes the entire value calculation.

A tool that only tracks ChatGPT is covering the vast majority of where your audience is actually asking AI for recommendations. Adding Perplexity, Gemini, AI Overviews, and Copilot gives you completeness — but the marginal insight from each additional platform diminishes. If your audience isn't heavily using Perplexity, paying a premium for Perplexity tracking is paying for data you won't act on.

Multi-platform coverage matters at scale. It matters for agencies managing multiple brands across different verticals where audience behavior varies. It matters for enterprise reporting where completeness is a compliance requirement.

For a single brand trying to answer "does AI visibility matter for us?" — it's overkill.

The real question most businesses need to answer first

Here's what I think gets lost in the feature comparison game: most companies haven't even established whether AI visibility moves their needle. They're evaluating tools before they've validated the premise.

That's backwards.

The smart move is to spend the minimum required to answer a binary question: is AI sending us traffic, leads, or brand awareness that we'd miss without it? If the answer is yes, you now have data to justify scaling up — more prompts, more platforms, higher frequency. If the answer is no (or not yet), you've spent $20 instead of $500 learning that.

This is exactly what makes the affordable end of the market interesting right now. You're not committing to a workflow. You're running a low-cost experiment. And the data you get back — a visibility score, a competitor breakdown, a topic-level map of where you're leading versus invisible — is enough to make the call.

What the whole category still gets wrong

Almost every tool in this space has built a strong measurement layer. They can show you where you're visible and where you're not. What none of them do well yet is tell you what to do about it.

The "recommendations" features that exist today are largely recycled GEO checklists: add structured data, create an llms.txt file, publish authoritative content. You could play bingo with them. The advice barely changes from one brand to the next, which defeats the purpose of personalized tracking.

A tool that connects to your actual site, diagnoses specific gaps, and gives you prioritized fixes — that's the next unlock for the category. Several tools have it on the roadmap. Beamtrace, for instance, is building an "Actions" feature that includes impact tracking after changes and an AI agent that works inside your site. It hasn't shipped yet, but the direction is right: the measurement is table stakes now. The action layer is where the real value will live.

So where does that leave you?

If you haven't started tracking AI visibility, the barrier to entry is now lower than a team lunch. The technology works. The category is real. The only remaining question is whether it's real for you.

Start with what you can afford to experiment with. Something in the $20–50 range answers the question that actually matters. If the data says yes, scale up with confidence. If it says not yet, you've lost almost nothing.

But spending $500 a month to answer a question you could answer for $20? That’s something worth thinking twice about.

Based on pricing and product data from March 2026. Tools and features may have changed since publication.