How to Choose the Best AI Visibility Tools for Your Marketing Stack

A buyer asks ChatGPT which vendors to shortlist and it spits out an answer that names three of your competitors, borrows your positioning to describe one of them, and never bothers mentioning you. And the most sweet treat of all is that it doesn't show up in any of the ways you measure now.

We evaluated the AI visibility tools built to catch this. That means software that tracks your brand's mentions and citations, then scores sentiment across the LLM answers your buyers now read alongside classic search results. Optimization and content-execution tooling is a separate category with its own tradeoffs, so this comparison stays on the monitoring layer, meaning who tracks what, how they score it, and what the numbers actually mean.

First, how we scored them.

How we evaluated

The AEO software category grew more than 2,000% since March 2025 in G2 category data, which means dozens of tools now claim to do the same job at wildly different depth. We scored each tool against seven criteria:

• Multi-engine coverage — whether the tool tracks ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude, and Microsoft Copilot, and whether the vendor gates any of those engines by plan or sells them as paid add-ons. Several do, and the add-ons change the real price.
• Citation vs. mention tracking — a mention is your brand named in the answer text, while a citation is your URL used as a source. They're different signals with different fixes, and the better tools separate them.
• Sentiment scoring — methods vary from frequency-weighted models to net scores on a -100 to +100 scale. The method changes what the number means.
• Competitor benchmarking — share of voice only helps when the vendor publishes the formula behind it.
• Prompt-level tracking — how many prompts you can track, whether you can customize them, and how often they re-run. Daily versus monthly cadence is a material difference.
• Reporting and integrations — BI connectors and agency-ready reporting, including Looker Studio and Search Console or GA4 hookups.
• Pricing transparency — we awarded points for published pricing and deducted them for demo-gated pricing.

The field at a glance

Here's how the tools compare on coverage and fit. We did include our own free-to-use tool CheckThat here for reference.

Three tools we'd shortlist first

Rather than force a single winner, we'll tell you which tool wins for which job. Profound for enterprise depth, AthenaHQ for competitive benchmarking, and CheckThat when you want real benchmark data before committing budget. All three publish enough methodology to audit their numbers, which is where several rivals fell down in our scoring.

Profound for enterprise depth

G2's first AEO Grid, published alongside that category-growth data, names Profound its only Leader, and the placement held up under our scoring.

• Coverage and cadence — it tracks ten answer engines, including all six majors plus Grok, Meta AI, and DeepSeek, and runs its prompts daily.
• Metrics — it publishes exact metric formulas. Visibility score is responses that include your brand divided by total responses including at least one brand, and share of voice is your mentions divided by total brand mentions across all responses.
• Sentiment — the model is frequency-weighted, so a positive claim mentioned 100 times carries ten times the influence of a negative claim mentioned ten times.

Data sourcing sets Profound apart. It builds on real user prompts rather than modeled keyword databases, and its Search Console integration ties AI answers back to actual query data. The fit is an enterprise brand team that needs the deepest citation data available and has an analyst to work it, because practitioner reviews describe the platform as data-heavy with a steep learning curve.

The free starter tier covers ChatGPT only. Paid pricing is largely demo-gated, so walk in budgeting for an enterprise line item rather than a tool-stack add-on.

AthenaHQ for competitor benchmarking

Every tool in this category claims share-of-voice tracking. AthenaHQ decomposes it into three sub-metrics, Mention SOV, Citation SOV, and Position SOV. That split matters operationally, because a competitor can beat you on mentions while you beat them on citations, and the fix for each gap is different. A single blended number hides which problem you have.

Coverage runs nine engines, including ChatGPT, Perplexity, AI Overviews, Gemini, Claude, Copilot, Grok, and DeepSeek, tracked at the level of mentioned, cited, position, and sentiment per answer. Reviewers praise the granular, actionable insights and regional segmentation, while the criticisms center on the credit system's complexity and the lack of a consolidated multi-brand view.

The fit is a growth or product marketing manager whose weekly job is side-by-side visibility against a named competitor set. There's a free tier and published paid plans, though the citation engine and API access sit behind the Enterprise tier, and there's no free trial of the paid features.

CheckThat for free benchmarking

CheckThat is our preferred free starting point in the category, and a disclosure is in order. GrowthX, the company behind this publication, built it.

It wins on budget because of the benchmark data you get before spending anything. Most freemium tiers give you a handful of prompts against your own brand. CheckThat gives you an open benchmark index covering 5,800+ brands across 172 categories, built on 2.6M+ AI responses, so you can see how your whole category performs in AI answers before you track a single custom prompt.

The free tier also covers custom prompt tracking across ChatGPT, Perplexity, Claude, and Google AI Mode, with paid plans adding depth on custom prompts and historical data. Pricing isn't published in structured tiers, so you'll have to ask. The fit is a team that needs to quantify the problem and benchmark against category peers before making the case for a paid platform. If you specifically need Copilot or AI Overviews coverage on a small budget, Otterly's Lite plan at $29/month for 15 prompts is the cheapest paid alternative we found.

Other options we considered

The remaining tools each solve a narrower problem, and a few solve a different one than their category placement suggests.

Scrunch AI, now Sitecore-backed, has the strictest measurement methodology in the field. Only direct answer-text mentions count, never brand names buried in cited URLs or snippets, which keeps its numbers conservative and defensible. Its most-praised feature is a GA4 integration that shows actual AI referral traffic by engine, which moves the conversation from visibility to attribution.

Peec AI is the agency and EU favorite, with unlimited seats on every plan, strong Looker Studio support, and multilingual tracking, though Search Console and GA4 hookups require custom API work. For a multi-client shop, unlimited seats plus Looker templates covers most of the reporting workflow out of the box, and that matters because agency margins die on per-seat fees.

Semrush's AI Visibility Toolkit and Ahrefs Brand Radar are the right answer if you already live in those suites, with one sharp caveat. Ahrefs updates ChatGPT, Perplexity, Gemini, and Copilot data on a monthly cadence, against daily cadence at Profound and Peec, and a monthly snapshot can't tell you whether last week's content push moved anything. Semrush's core reports skip Claude and Copilot entirely, so check that the engines your buyers actually use are in the box before you bundle.

Conductor is building a credible enterprise system of record, with an API-first data approach and eight engines across 160+ countries, though its redesigned platform and prompt groups remain in limited release. Worth a look if you're already a Conductor shop, and worth waiting on if you're not.

Beyond these, a wave of newer entrants shows up in vendor comparison posts, and several turn out to be agencies or ad-tech rather than monitoring software. Verify the category before you take the meeting. If the pitch leans on self-reported client metrics instead of a methodology page, that tells you most of what you need to know.

How to choose

Start from what your current stack can't see, then work forward to what you need the new tool to change.

Your rank tracker misses this channel entirely, and the limits are specific:

• Google Search Console has a documented blind spot here. It doesn't record when your content is cited in an AI Overview, or whether an AI Overview appeared for a query at all.
• Rankings and click-through rates describe the classic results page, and practitioner analysis is blunt that AI-driven search needs its own visibility metrics.
• Generative engines publish no query-volume APIs, and their outputs are non-deterministic, so two runs of the same prompt can name different brands.

Track mentions and citations first, then use share of voice to compare against competitors. We've broken down measuring AI share of voice separately, so we won't re-teach the metrics here. There's also an observer-effect risk, where heavy automated monitoring pollutes your own analytics with self-generated data. We haven't seen a vendor publish a mitigation methodology for it yet, so ask about it on the sales call.

The mention-versus-citation split should also drive what you do after the numbers land. A mention gap usually means the models don't associate your brand with the category, which is an entity and coverage problem. A citation gap means your pages aren't source-worthy for the answers being assembled, which is a content depth and structure problem. Knowing which one you have changes the brief you hand your content team, and it's the first thing we look at when a new engagement starts.

On engine selection, start where your buyers actually ask questions. For most teams that means Google AI Overviews and ChatGPT first, with Perplexity, Gemini, Claude, and Copilot added based on your audience. Watch the plan details here, because several tools gate Claude and Copilot behind add-ons or higher tiers, and that add-on math is frankly where budget surprises live.

Don't buy on the acronym either. Most vendors treat GEO and AEO as synonyms, and Google's May 2026 guidance folds optimizing for generative AI search back into ordinary SEO. In one 2026 survey, 81% of marketers still say "SEO" internally, while 12% search for "GEO" and 3% for "AEO." The labels churn faster than the work does. Strong SEO fundamentals produce strong AEO results, so evaluate tools on measurement quality rather than on which acronym the homepage uses.

Read the metric formulas before comparing numbers. Share of voice uses materially different denominators across platforms. Profound divides your mentions by total brand mentions across all responses, Scrunch uses a fixed brand-plus-competitors denominator that always sums to 1, and Ahrefs models impressions weighted against Google search volume and calls the output directional. A 20% score means different things in different tools, so pick one methodology and track your trend inside it. If a vendor won't show you the arithmetic, that's your answer.

If you run an agency, white-label capability sorts the field fast. Scrunch's agency plan at $500/month offers fully white-label client outputs, and several mid-market tools advertise white-label reporting as well, while Otterly offers only a Looker Studio workaround at this time. For in-house teams extending an existing stack, Semrush and Ahrefs win on friction because the AI visibility data sits next to your keyword and backlink tooling.

Run a 90-day pilot before you commit to an annual contract. Fix a prompt set that mirrors how your buyers actually phrase questions, baseline your mentions and citations in week one, and don't touch the prompt set mid-pilot, because a moving target makes the trend unreadable. Most of the vendors here offer monthly plans or free tiers that make this cheap, and a quarter of clean trend data tells you more than any demo will.

Whichever way you lean, a few questions separate the strong demos from the weak ones fast:

• Formula transparency — ask the vendor to walk through the share-of-voice arithmetic on a live account.
• Engine gating — confirm which engines your quoted plan actually includes, and what each add-on costs.
• Refresh cadence — daily, weekly, or monthly, per engine, in writing.
• Observer effect — ask how their monitoring volume avoids polluting your analytics.

What monitoring alone won't fix

Then there's the question none of the dashboards answer. What happens after you see the gap?

Every monitoring tool we reviewed stops at measurement and leaves content execution to you, a limitation practitioner reviews flag across the entire category. You'll see that a competitor owns the citations for your best-fit prompts, and the tool won't write, review, or publish the pages that change it. In our experience, that handoff is where visibility projects stall. The finding sits in a dashboard, the content team has its own queue, and the gap is still there next quarter. We've watched teams renew a monitoring subscription twice without shipping a single page against its findings, which is money spent measuring a problem instead of fixing it.

We built GrowthOS to close that gap. It tracks up to 2,000 prompts per month across ChatGPT, Claude, Perplexity, and Google AI Overviews, scores your brand on Presence, Reputation, Perception, and Influence, and feeds those findings directly into a Creation layer producing up to 100 human-approved content pieces per month, with results flowing back through Insights to reprioritize what gets made next. If you've just recognized your own dashboard-to-nowhere problem in that description, book a demo and see the loop running on a team like yours. Engagements start from $6,000/mo.