Every platform in this category sells the same promise: find out whether ChatGPT, Gemini, Perplexity or Claude names your brand when a buyer asks a real question. What separates them is much harder to see from a marketing page. Some only watch one engine on the entry plan. Some meter usage in credits that drain faster than the pricing calculator suggests. A few actually do something with the data once it lands.

This comparison covers eight platforms a serious buying team would shortlist right now. Each gets the same treatment: what it measures, what the entry plan really includes, where it stops being useful, and who it fits. Prices were checked against vendor pricing pages in August 2026. This market changes monthly, so treat every figure as a starting point for your own check rather than a settled fact.

How these eight platforms were compared

Six criteria, weighted toward what a team feels in month three rather than what looks good in a demo.

How the editorial score is built

Four of those six criteria are scored on a 0 to 5 scale and combined into the editorial score out of 5. Evidence quality and action layer carry 30% each, engine coverage 25%, setup effort 15%. The weighting is deliberate: engine counts change every quarter, but whether a number can be traced back to a raw answer, and whether anything gets fixed after the dashboard loads, is what a programme still depends on a year later.

Cost honesty and free access are reported as facts rather than scored, because a price and a trial length are things a buyer can verify in a minute and they belong in the pricing table, not in a rating. Every platform below carries the same four-bar scorecard on the same scale, so the panels can be read against each other rather than admired one at a time.

Scores are editorial judgment against this rubric, informed by public review data on G2 and Capterra and by vendor documentation. One platform per brand, so SEO suites that bundle a visibility module appear once rather than three times.

Full feature and pricing table

Prices verified against vendor pricing pages in August 2026. Engine counts refer to what is included without paying an add-on.

Visual comparison of all eight tools

Same shortlist, easier to scan. The four bars on each tile are the four scored criteria in the same order every time: evidence quality, action layer, engine coverage, setup effort.

Best overall · Free public tools with no account · Paid plans from $39 a month · Editorial score 4.8 / 5

The only platform here scoring 5 on both evidence and action: every number opens into the raw answer, and the same data carries through to published content.

InsightWonder sits at the top of this list for one structural reason. Most tools in the category stop at the dashboard. This one carries the same evidence through to content and then to the channels where AI systems actually pick up citations, which is where the earned media data says most of the influence lives.

The measurement side is conventional in scope and unusually strict in method. Buyer questions are generated across research, comparison, trust and purchase intent, then asked of the supported engines, currently ChatGPT, Gemini, Perplexity, Claude and Grok. Three design choices stand out. Questions containing the brand name are excluded from visibility scoring, because asking a model about a brand by name inflates the mention rate without reflecting real demand. A question that has not been run against a model stays marked as unmeasured instead of quietly counting as zero. And citations resolve from markers inside the answer text to the exact URL, question and engine, so a number can be opened back into the raw answer that produced it. Crawlability is probed by requesting pages as GPTBot and other AI crawlers rather than trusting a robots file.

The half that most competitors do not have: Opportunity Discovery finds valuable questions where AI still recommends someone else, Content Creation turns confirmed facts into GEO articles, FAQ sets, comparison pages and press releases with deterministic scoring and paragraph rewrite, and Media and Distribution pushes approved work out across social platforms, news media and community channels. External publishing is draft-first and needs human confirmation, which matters if a brand cannot afford an automated post going out unreviewed. There is a Shopify app for merchants who want FixPacks and confirmed write-back inside the store admin.

On price it lands in the lower third of the category while doing more than most of the upper third. The free public tools run a real snapshot, a crawler check, an llms.txt validation and a schema extraction on any URL without a signup. New accounts get a full-feature trial with no card. Paid plans start at $39 a month for one site and 30 tracked questions, then $149, $389 and $899 as sites, questions and answer runs scale, with Enterprise custom. Media placement is deliberately kept out of the subscription and billed pay per use through a wallet, so software cost and paid placement never blur into one figure.

Best for: in-house growth teams, DTC and ecommerce brands, and agencies that need the work to end in published, distributed content rather than a monthly slide.

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Best for enterprise answer analytics · $99 to $399 a month billed yearly · Editorial score 4.5 / 5

Evidence quality is the highest in the category. Engine coverage is scored on Growth, the plan most buyers actually land on, rather than the single-engine Starter.

Profound is the platform most enterprise buyers benchmark everything else against, and the reputation is earned on data depth. Daily refreshes, long time-series tracking that ties visibility movement back to specific content changes or PR activity, source attribution, sentiment, share of voice, and agent analytics covering how AI crawlers move through a site. With around $58.5 million raised and a G2 rating near 4.5, it is not a small bet by anyone.

The pricing structure is where care is needed. Starter is $99 a month billed yearly and tracks ChatGPT only, 50 prompts, one seat. Growth is $399 a month billed yearly and adds Perplexity and Google AI Overviews for 100 prompts, three seats and 400 agent credits, with a 7-day trial. Claude and the full engine set live behind custom Enterprise pricing. Both public tiers are annual commitments, so the real number to compare is $1,188 or $4,788 a year, not the monthly sticker.

The recurring theme in user feedback is that the intelligence outruns the capacity to act on it. One G2 reviewer noted that the pricing structure tempts teams into tracking more topics than they can respond to, which makes the programme less focused rather than more. That is a fair warning for a lean team. Profound rewards organisations that already have SEO analysts, writers and a content pipeline waiting for direction.

Best for: enterprise marketing organisations with the analyst headcount to convert dashboards into shipped changes.

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Best for AI crawler and agent traffic data · Core $250 a month · Editorial score 4.4 / 5

Crawler-level logs push evidence to a 5. Engine coverage is capped by the four engines on Core, with the rest sitting behind Enterprise.

Scrunch approaches the problem from an angle almost nobody else covers properly. Alongside mention and citation tracking it records which AI bots visited a site, which pages they read, how often, and then connects that crawl activity to the referral traffic AI sources send through analytics. For a team trying to work out why a specific page is or is not being cited, that pairing is far more diagnostic than a visibility score alone.

The Agent Experience Platform is the ambitious piece: a structured, machine-readable version of a site served to AI crawlers in parallel with the normal pages, organising brand knowledge into entities, attributes and verified claims. Compelling for JavaScript-heavy sites that crawlers struggle to parse. It has also been in limited availability for a while, so it should be treated as roadmap rather than a reason to buy today.

Pricing is at the top of the self-serve range. Core is $250 a month covering four engines, with an agency tier at $500 and custom Enterprise above that. Claude, Gemini, Meta AI, Grok and AI Mode sit on the Enterprise side. There is a 7-day trial with no card. The prompt credit system deserves attention: every engine tracked consumes against the prompt allowance, so 100 prompts across five engines uses 500 credits, which is not obvious from the pricing page. Scrunch was acquired by Sitecore in 2026, and while nothing has been announced about the self-serve plans, it is a reasonable thing to raise before signing an annual contract.

Best for: technical SEO and enterprise teams that need crawler evidence, not just answer counts.

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Widest engine coverage per dollar · $20 entry, $99 working tier · Editorial score 4.3 / 5

The only 5 for engine coverage on this list. The action layer is where it gives ground, because it reports and then stops.

Rankscale is the value pick, and it earns that with breadth. More than 17 engines are available on every tier, including Claude, Grok, DeepSeek, Mistral, Copilot, Google AI Mode and AI Overviews. Most rivals gate the interesting engines behind an upgrade. The citation analysis is the strongest part of the product: cited domains, cited URLs, content categories and brand citation share tracked over time, which is genuinely useful when trying to work out which third-party sources influence answers in a category.

It is a small bootstrapped product from Vienna that ships fast, with a public changelog showing near-weekly releases, a REST API, a Looker Studio connector and an MCP server. Enterprise logos appear on the site, which is unusual for a tool at this price.

The catch is the credit model. The $20 Essentials plan ships with zero credits and cannot run a prompt on its own, so the honest entry price is the $99 Pro tier with 1,200 monthly credits. Each engine query typically costs 0.25 credits, meaning cost equals prompts times engines times cadence. Tracking 20 prompts across 10 engines daily works out to about 1,500 credits a month, which already exceeds Pro. Growth is $385 and Enterprise $780. The free site audit runs without registration, which makes a first look easy.

Best for: analytically minded SEO teams and agencies that want maximum engine coverage and will do the credit maths.

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Tracking joined to content production · From $99 a month self-serve · Editorial score 4.1 / 5

A strong action layer from the content suite, paired with the joint-lowest evidence score here. That trade is the whole product in one panel.

Writesonic came at AI visibility from the content side rather than the analytics side, and that shapes the whole product. It tracks across roughly ten AI platforms including ChatGPT, Google AI Overviews, Claude, Gemini and Perplexity, identifies where a brand is missing from answers, then recommends and drafts the content changes meant to close that gap. The Content Strategy Planner scores a site against competitors and suggests topics likely to earn citations, with prompt demand estimates pulled from a very large pool of AI conversations.

For a content team already publishing weekly, the appeal is obvious. One tool, one workflow, no export step between the insight and the brief. The self-serve pricing page starts at $99 a month, with higher tiers adding prompt volume and content generation. Third-party roundups quote different figures for different plan names, which is a reminder to read the live page rather than a review before budgeting.

The honest trade-off is analytical depth. Compared with the dedicated monitors, tracking is lighter, and the optimisation recommendations are algorithmically generated, which means some land and some are generic. Teams that need a defensible measurement baseline for a board deck will find the numbers thinner than Profound or Rankscale would give them.

Best for: content-led teams whose bottleneck is production rather than measurement.

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Enterprise activation, not just measurement · Custom pricing · Editorial score 4.0 / 5

The highest action score on the list, because the change is executed for you. The lowest setup score, because nothing starts without a scoping cycle.

Brandlight is built for organisations that do not want to watch a number, they want to change what models say. The platform covers eleven leading AI engines and pairs measurement with an executed activation programme and a hands-on strategy team. It earned Leader status in the CB Insights ESP ranking for generative engine optimisation and has picked up senior marketing testimonials, which tells you where it is being sold.

The interesting part of the positioning is that measurement is treated as the input to a service, not the deliverable. For a Fortune 500 brand operating across several markets with brand drift showing up differently in each one, that model makes sense. Somebody has to own the work of correcting how a model describes a company across eleven surfaces and multiple languages, and most in-house teams simply do not have that capacity.

Everything about it is enterprise-shaped, including the absence of any public price. There is no self-serve tier and no trial, so evaluation happens through a demo and a scoping conversation. If a team is comparing this against a $99 tracker, the comparison is not really like for like: one is software, the other is software plus people.

Best for: large multi-brand organisations that need AI narrative correction handled as a managed programme.

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Brand perception measurement at scale · Custom, reported from about $800 a month · Editorial score 3.9 / 5

Sampling over a million prompts per brand earns a top evidence score. Sales-led onboarding is what drags the composite below the tools above it.

Evertune answers a different question from most of this list. Not whether a brand appears, but how models frame it. A model can name a company first and still describe it as expensive and dated, and that mismatch is invisible to a tool that only counts mentions. The AI Brand Index combines visibility frequency with ranking position, and the platform reports on the language models use when describing a brand.

Scale is the differentiator. The methodology now runs over a million prompts per brand each month, up roughly tenfold from its earlier approach, with coverage extended to DeepSeek and Copilot. Shopping Intelligence, added in 2026, tracks how AI shopping assistants recommend products and where competitors dominate a category, which matters for retail and consumer goods. Founded by former Trade Desk executives and funded to around $19 million, the company has an advertising-industry outlook that shows in the product.

Pricing is custom with no public figure. Third-party reviews report a Pro tier around $800 a month and enterprise engagements running considerably higher. That puts it out of reach for most growth-stage companies, and the honest read is that organic-only teams will not need this layer yet. Brand and CMO-level buyers in high-consideration categories are the fit.

Best for: brand teams in high-consideration categories that care how AI characterises them, not just whether it lists them.

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SEO rank tracking with an AI layer · From $32 a month plus add-on · Editorial score 3.7 / 5

The flattest profile on the list. Fastest setup of the eight, and nothing else above 3.5, which is what an add-on rather than a core product looks like.

Nightwatch is the path of least resistance for a team that already lives in rank tracking. It monitors keyword positions across search engines with location precision across a very large number of places, runs site audits, tracks SERP features, and has added LLM visibility so a team can see how content shows up inside AI-generated answers from ChatGPT, Claude and Gemini in the same dashboard as the organic data.

Putting both data sets side by side is genuinely useful. When AI Overview citations increasingly come from pages outside the organic top ten, seeing where the two diverge for the same term is a real diagnostic. Very few dedicated AI tools show classic rankings at all.

Entry pricing starts around $32 a month billed annually for the core platform with 250 keywords, and the AI tracking layer is typically an add-on that reviews report at roughly $99 a month. A 14-day trial is available. The trade-off is depth. Prompt-level analysis, citation source breakdowns and competitor share of voice are thinner than any pure-play tracker on this list, and public documentation about exact engine coverage is thin enough that a trial is the only sensible way to confirm fit.

Best for: SEO teams already on Nightwatch who want early AI signals without adding a tenth login.

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What these tools actually cost

Published entry prices tell a misleading story on their own, so the chart below shows the lowest publicly listed monthly figure for each platform, followed by a second view of what is included at that price.

Now the same platforms measured on what the entry plan buys. This is the chart that changes shortlists, because a cheap plan covering one engine is not cheaper than a mid plan covering nine, it is just smaller.

Put the two charts beside each other and the pattern is clear. Price and coverage are only loosely related in this category. The cheapest listed plan cannot run a prompt without credits. The best-known platform gives one engine at $99. Meanwhile a $39 plan covering five engines including Claude and Grok sits in the middle of the price chart and near the middle of the coverage chart, which is roughly where value tends to live.

How to choose without burning a quarter

Most evaluations go wrong in the same place. A team picks a tool, watches a number for six weeks, and then discovers the number cannot be defended internally or acted on externally. A better sequence:

Write the prompt set before looking at any tool

Twenty to forty questions a real buyer would type, spread across research, comparison, trust and purchase intent. This is the single highest-leverage decision in the whole programme, and it is tool-independent. Trackers with different prompt sets will disagree about the same brand, and that disagreement is usually the prompt set rather than the software.

Trial two tools on the same prompts, not one tool for twice as long

Run the identical questions through two platforms in the same week. Expect the scores to differ. What matters is whether each tool can show the raw answer behind its number, because a score with no answer log underneath it is not evidence.

Price the coverage, not the plan

Take the engines your buyers actually use, then find the cheapest plan that includes all of them without add-ons. Do the same for prompt volume at the cadence you intend to run. Weekly detection on 30 questions is a very different bill from daily detection on 200.

Decide who does the work before the invoice arrives

A tracker that only reports puts every finding into somebody's backlog. If the team has no writer or no distribution route, choose a platform that closes that loop, or budget separately for the people who will. Insight with no execution path is the most expensive form of visibility spending.

Five mistakes buyers keep making

Counting a zero that was never measured. If a question was not run against a model, it is unmeasured, not a zero. Tools that blur the two produce charts that look like a decline when nothing declined.

Tracking branded prompts. Asking a model about a company by name almost always returns the company. Including those prompts inflates a visibility score and hides the questions where a competitor is winning.

Treating one run as a reading. Single answers are noisy and engines disagree with each other far more than people expect. Repeated sampling is the product. A one-off lookup is a screenshot.

Assuming a citation means a recommendation. A page can be cited as a source while the answer recommends someone else entirely. Mentions and citations need separate metrics or the reporting quietly flatters the brand.

Buying annual before knowing whether there is a problem. A free snapshot answers the diagnostic question in minutes. Running that first, then choosing a plan against a real gap, avoids paying four figures to learn something a public tool would have shown for nothing.

FAQ

How often should AI visibility be measured?

Weekly is the sensible default for most brands. Daily sampling burns credits fast and rarely changes a decision, while monthly leaves too much time between a content change and the signal that it worked. Enterprise programmes with heavy PR activity sometimes justify daily runs. If a tool bills by credits, cadence is the setting that moves the invoice most.

Is a free AI visibility checker enough to run a programme?

For a first diagnosis, yes. A free snapshot will tell a team whether it appears in category answers and who appears instead, which is enough to decide whether to invest at all. It is not enough for an ongoing programme, because repeated sampling over time is what turns single answers into a trend. Use the free layer to size the problem, then pay for continuity.

Why do two tools report different visibility scores for the same brand?

Different prompt sets, different sampling schedules, different engines and different scoring rules. Two platforms can both be measuring correctly and still disagree, which is why comparing absolute scores across vendors is meaningless. Pick one tool as the system of record, keep the prompt set stable, and compare against your own history rather than against another dashboard.

Do these platforms work outside English-speaking markets?

Coverage varies a lot. Some tools report a single global number, while others support country and language segmentation as a paid feature. Anyone selling into several markets should confirm regional prompt support during a trial rather than assuming it, because answers genuinely differ by country and a blended global score can hide a serious gap in one market.

How long before a GEO programme shows movement?

Technical fixes such as crawler access or structured data can register within weeks. Content and earned media work takes longer, commonly one to three months, because models need to encounter and trust new sources before those sources change answers. Anyone promising a shift in days is describing prompt-set manipulation rather than real visibility.

Can AI visibility be tracked manually without buying anything?

It can be started manually. Asking each assistant the same ten questions weekly and logging the results in a sheet is a legitimate baseline for a very small brand. It falls apart at scale, because manual sampling is too small to be statistically meaningful and nobody keeps it up past month two. Manual tracking is a proof of concept, not a system.

Which team should own AI visibility internally?

Most often SEO or organic growth, because the measurement discipline is closest to what that team already does. The complication is that the work spans PR, content and sometimes product marketing, since citations come largely from earned sources. The teams that make progress usually assign one owner for the numbers and a standing route into whoever produces and places content.

Are AI visibility tools worth it for small businesses?

It depends on whether the category is one people ask assistants about. A local service business in a low-consideration category may see very little AI-driven discovery. A software product, a considered consumer good or anything with comparison-heavy research behaviour is a different story. Run a free snapshot first, and let the size of the gap decide the budget.

Sources

1. Semrush and Adobe, 2026 AI Visibility Index, 126 million US AI search prompts analysed. businesswire.com
2. Semrush newsroom release on the expanded 2026 AI Visibility Index. semrush.com
3. AI search statistics compilation covering zero-click behaviour and AI referral share, 2026. superlines.io
4. AEO and GEO statistics including Conductor AI Overview coverage data and earned media citation share, 2026. instantpress.co
5. 2026 AI search traffic report on assistant referral share across brand sites. higoodie.com
6. Profound plan ladder and limits, verified August 2026. trakkr.ai
7. Scrunch pricing page, Core and agency tiers. scrunch.com
8. Scrunch review covering the Sitecore acquisition and the 2026 price list. get-ryze.ai
9. Rankscale pricing, credit model and engine coverage, verified July 2026. meev.ai
10. Cross-vendor pricing check on AI visibility platforms, August 2026. ooky.ai
11. Writesonic AI Search Visibility pricing page. writesonic.com
12. Brandlight comparison of AI visibility tools, engine coverage and positioning. brandlight.ai
13. Evertune AI Brand Index product documentation. evertune.ai
14. AI search rank tracking tool roundup including Nightwatch plan detail. radarkit.ai
15. Category pricing overview with per-vendor source links, July 2026. acromatico.com
16. InsightWonder product and pricing pages. insightwonder.com