How to Track Your Brand in AI Search: A Practitioner’s Breakdown (With Tools Compared)

Google Search Console tells you your impressions, clicks, and average position. AI search is a black box by default. Here’s how to fix that — and what it actually costs to get started.

Why AI search is a blind spot, not a trend piece

There’s a category of lost lead that doesn’t appear anywhere in your analytics. Someone opens ChatGPT and types “best project management tools for small teams” or “affordable CRM for service businesses.” The model responds with three to five names. If yours isn’t one of them, that person never visits your site. They never hit your pricing page. They never enter your pipeline. The lead simply didn’t exist for you — it went straight to whoever ChatGPT decided to recommend.

With Google, you can open Search Console and see where you stand: impressions, clicks, average position. You have data to work with. AI search is a black box by default. Unless you’re actively monitoring it, you have no visibility into whether you’re being recommended or completely ignored across the queries that matter to your audience.

The volume question also has a clear answer. ChatGPT accounts for roughly 87% of all AI referral traffic to websites right now, according to Conductor’s 2026 benchmarks. Perplexity, Gemini, and the rest split what’s left. If you’re only going to track one AI platform to start, you already know which one.

What AI visibility tracking actually measures

Every tool in this category does the same thing mechanically: it sends prompts to LLM APIs, records whether your brand appears in the response, and tracks that over time. The output is typically a visibility score, a share of voice breakdown against detected competitors, and a prompt-level view of where you appear and where you don’t.

The value isn’t in the API call itself. It’s in turning “I think AI mentions us sometimes” into “we’re visible on 60% of value-based queries and invisible on discovery prompts.” That distinction is what makes the data actionable.

Worth stating clearly: no tool in this space has proprietary technology. Every platform hits the same LLM APIs and parses the same responses. What you’re paying for is coverage (which AI platforms), frequency (how often it checks), prompt volume, and how well the dashboard organizes the output. Evaluate on those axes — not on marketing copy about AI-powered insights.

How to set up tracking: the methodology

The setup process is consistent across tools. Here’s how to do it properly.

1. Define your prompt set

A prompt set is the list of questions you’re asking the AI on a recurring basis to measure your visibility. The composition matters more than the count. A useful starting breakdown:

• Branded queries: “Best [your category] for small business,” “top [your category] tools in 2026.” These tell you whether ChatGPT knows you exist in your core market.
• Discovery queries: “How do I [solve the problem your product solves],” “what should I look for in a [your product category].” These tell you whether you appear at the top of the funnel — before the buyer even knows what category to search.
• Competitor queries: “Is [main competitor] worth it,” “[competitor] alternatives.” These tell you whether you show up when buyers are actively evaluating your competition.

If you’re on a limited prompt plan, weight toward discovery queries. Branded query visibility is useful to know; discovery visibility is where the revenue gap actually lives.

1. Choose your starting tool

The lowest-friction entry point is Beamtrace — free tier, no credit card, no trial that auto-converts. It’s backed by the Elfsight team (13 years of SaaS, 3M+ active users), which matters when evaluating whether a free tier from a startup will still exist in six months.

One non-obvious thing to know before you start: Beamtrace pre-fills your prompt slots with auto-generated questions. Your allocation arrives fully used. You can delete the defaults and replace them with your own — the quota frees up — but it’s not obvious from the UI. Do this before you assume you need to upgrade.

1. Read the dashboard

Three numbers to focus on:

• Visibility Score: 0–100, based on how often your brand appears across your tracked prompts. Zero means ChatGPT genuinely doesn’t mention you. 40–60 means partial visibility with clear gaps.
• Share of Voice: How the visibility pie splits between you and detected competitors. This is the number that tells you how much ground you need to make up — and against whom.
• Topic breakdown: Where you’re Leading vs. Invisible, prompt by prompt. If you’re visible on branded queries but invisible on discovery prompts, that’s a specific, actionable content gap — not just a low score.

1. Decide when to upgrade

Don’t upgrade because the dashboard showed a low score. Upgrade because you’ve made content changes, need faster feedback loops, or have outgrown your prompt allocation. The tool should earn your money — not just ask for it because the score is low and the upgrade button is right there.

Tool landscape: what you’re choosing between

The market has fifteen-plus tools at this point. Here’s the concise version for a practitioner deciding where to start:

The underlying technology is identical across all of them. Platform coverage, tracking frequency, and prompt count are the real differentiators. The practical decision: if you’re testing whether AI visibility matters for your business, start at the free or $20 level. If you already know it matters and need broader coverage, LLM Pulse or Otterly. If you need daily tracking with flexibility on which platforms to monitor, Peec AI. Match the tool to the question you’re actually trying to answer.

Most tools offer 15–20% discounts on annual billing. Pricing verified March 2026.

Where the category still falls short

Every AI visibility tool today has a solid measurement layer. What none of them do well yet is tell you what to do about what you’re measuring — in a meaningful, personalized way.

The “recommendations” features, where they exist, are recycled GEO checklists: add structured data, create an llms.txt file, “publish authoritative content.” The advice is nearly identical regardless of your actual situation. You could play bingo with them across any three tools.

What the category actually needs is a tool connected to your site’s technical reality that produces specific, prioritized fixes — not generic best practices. Several platforms have this on their roadmap. Beamtrace’s planned Actions feature (visibility-gap-based recommendations, impact tracking after changes, one-click automation) is one of the more interesting approaches in the pipeline. None of it has shipped yet. But the Elfsight team’s track record of shipping finished products — rather than perpetual roadmap items — makes this worth watching.

The methodology here is simple and the starting cost is low. Sign up for a free tier, build a prompt set that covers branded, discovery, and competitor queries, and let a month of weekly data tell you whether AI visibility moves the needle for your business. If it does, you’ll have real numbers to justify a bigger tool. If it doesn’t, you’ve spent nothing to find out.