What AI Visibility Tools Cost Per Tracked Prompt

01Entry price is the wrong unit

The loudest complaint about this category is not that the tools are bad. It is that the pricing model punishes the exact behaviour the tools require. Three separate founders announced free alternatives within the same period, each naming the same trigger.

Note the precise wording: when you want to track lots of prompts. Not when you add users, not when you add competitors. Prompts. A second founder posting in r/startupaccelerator described the same trigger, noting that once you start tracking a decent number of prompts across multiple AI engines the pricing can climb very quickly.

That is a specific, measurable complaint, and it is invisible in every comparison that ranks tools by entry price. So here is the arithmetic nobody publishes. All figures below come from vendors’ own published pricing pages, verified in our existing pricing teardowns and linked at each point so you can check them.

One note on method before the numbers. Vendors change pricing in this category frequently, so treat every figure as accurate at the time it was read rather than permanent. What does not change is the arithmetic, and the arithmetic is the point. Once you can convert any published price into a cost per prompt per engine, you can evaluate a tier that did not exist when this was written.

02Cost per prompt, calculated

Divide the published monthly price by the published prompt allowance. That is the whole calculation, and almost no vendor presents it.

Two things jump out. First, Otterly is the only vendor here whose per-prompt cost falls meaningfully as you scale, from about $1.93 at entry to about $1.22 at its $489 tier, with add-on prompts cheaper still at about $0.99 each. That is conventional volume pricing and it makes forecasting easy.

Second, and much stranger, Profound moves the other way. We come back to that below because it is the single most consequential pricing detail in this article.

03Cost per prompt per engine, the honest unit

Cost per prompt is still not quite fair, because a prompt checked across eleven engines is doing far more work than a prompt checked across three. Divide again by engine count and the picture changes substantially.

The Rankscale figure needs its working shown, because it is the most favourable number in this article and should not be taken on trust. Rankscale’s published pricing lists Pro at EUR 99 for 1,200 credits, and its credit model meters at roughly 0.25 credits per engine per prompt across 11 engines. One prompt checked across all 11 engines therefore consumes about 2.75 credits. Rankscale’s own guidance is that EUR 99 buys roughly 100 prompts checked weekly across all 11 engines, and the arithmetic supports it: 100 prompts, weekly, at 2.75 credits works out near 1,196 credits against the 1,200 included. The full breakdown is in our Rankscale alternatives guide.

04The tier that gets more expensive as you scale

Profound publishes two prices on its own page: $99 for 50 prompts and $399 for 100 prompts. Both figures are checkable today and we verified them in our Profound vs Peec AI comparison.

Doubling the prompt allowance quadruples the price. Per prompt, the higher tier costs about twice as much as the lower one. That is the reverse of how volume pricing normally works, and it is unusual enough that it should not be read as a criticism without asking why.

The most likely explanation is that the two tiers are not selling the same thing. Higher tiers in this category typically bundle additional engines, seats, integrations or analytics depth, and Profound is positioned at the enterprise end, arriving with compliance work already done including SOC 2 per LLM Pulse. If the $399 tier includes materially more than 50 extra prompts, the per-prompt comparison is unfair to it.

Which is exactly why this belongs in your demo rather than your spreadsheet. Ask the vendor to itemise what the additional $300 buys beyond the 50 additional prompts. A clear answer resolves it. A vague answer tells you the tiering is designed around willingness to pay rather than cost to serve, which is legitimate but changes how hard you should negotiate.

The general lesson generalises well beyond Profound: in this category, a price is only comparable when you know the tier, the engine count and the billing term. Most published comparisons name none of the three, which is how the same product ends up quoted at wildly different numbers across competing guides. We worked through that problem in our B2B SaaS buyer’s guide.

05Credit models versus flat prompt tiers

Two pricing philosophies compete in this category and the choice between them matters more than most feature differences.

Flat prompt tiers, as Otterly uses, publish a price and a prompt count. $29 for 15, $189 for 100, $489 for 400, with extra prompts at a stated $99 per 100. You can forecast this on a napkin, and the ceiling is knowable. The cost is that you pay for the allowance whether you use it or not, and per-unit rates are higher.

Credit models, as Rankscale and AthenaHQ use, publish a credit pool and a consumption rate. Rankscale’s published tiers run EUR 20 Essentials, EUR 99 Pro for 1,200 credits, EUR 385 Growth for 5,500, and EUR 780 Enterprise for 12,000, metering at roughly 0.25 credits per engine per prompt. AthenaHQ publishes Essential free with 300 credits and Starter at $295 for 3,600 credits.

Credit models are genuinely more honest about what drives cost, and they are cheaper per unit at the top end. Their weakness is forecasting: your bill now moves with three variables at once, being prompt count, engine count and check frequency. Increase weekly checks to daily and consumption multiplies by roughly seven without anyone approving a budget change. Wellows flags exactly this risk on Rankscale, noting that credit usage needs watching at scale.

06What the free tiers really give you

Free tiers in this category are unusually real, and for a company deciding whether it has a visibility problem at all, they are the correct first step.

AthenaHQ publishes an Essential tier at no cost with 300 credits across five engines including Claude, and unlimited team members. Its pricing page describes that as $25 of free credit. The inclusion of Claude matters more than it appears, since Claude is commonly sold as a paid add-on elsewhere. The catch is the cliff on the other side: the next published tier is $295 per month for 3,600 credits, with nothing in between. We covered that structure in our AthenaHQ alternatives guide.

At the cheap paid end, HubSpot AEO at $50 per month, or $45 annually, buys 25 prompts across 3 engines. That is the cheapest verified paid entry we have found, and its limitation is honest and important: 25 prompts across 3 engines is a sample large enough to confirm a gap you already suspect and too small to discover one you do not.

That distinction is the right way to think about every free and entry tier here. They answer the question “do we have a problem”. They do not answer “where exactly is it”. Budget accordingly, and do not mistake a confirmed suspicion for a completed audit.

07Budgeting for a programme rather than a trial

Put the two halves together and the real number appears. LLM Pulse recommends tracking 50 to 150 prompts, segmented by model and run weekly. Price that honestly at the midpoint of 100 prompts.

So a genuine programme, not a trial, lands somewhere between roughly EUR 99 and $399 per month depending on model and engine breadth. That is the number to take to a budget conversation. Comparing $29 entry tiers is comparing prices nobody running a real programme will pay for long.

It also explains the founder complaints precisely. Someone who signs up at $29 for 15 prompts, discovers that 15 prompts cannot cover category, comparison and problem-first patterns across their market, and then prices the tier that can, experiences exactly the climb described in those threads. The pricing is not deceptive. The entry tier is simply sized for evaluation and marketed as if it were sized for operation.

08The third pricing model: billing per engine

A third structure exists that neither flat tiers nor credits describe, and it is the most expensive of the three at any serious scale.

Ahrefs Brand Radar publishes $199 per month per AI engine index, or $699 per month for all of them, and that sits on top of an Ahrefs suite plan rather than replacing it. Wellows quotes the all-in figure at $828 or more per month once the suite is included, and separately attaches a documented accuracy concern to the product, which is worth investigating directly at that price.

Per-engine billing inverts the incentive that makes credit models attractive. On credits, adding a tenth engine costs a fraction more per prompt. On per-engine billing, each additional engine is a fixed $199 per month regardless of how many prompts you run through it. That structure rewards very high prompt volumes across few engines and punishes the opposite, which is the profile most early-stage teams actually have.

It also has one genuine advantage worth naming: your bill does not move when your prompt count does. For a large team that expects to expand its prompt set continuously, a fixed per-engine fee is the only one of the three models with no volume cliff in it. Whether that is worth roughly $828 per month depends entirely on scale, and for most teams reading this it will not be. The comparison against standalone tools is in our Ahrefs Brand Radar alternatives guide.

One further category deserves a mention: vendors that publish nothing at all. Peec AI publishes no pricing on its page, and Frase publishes add-on rates without a plan price. A vendor that will not publish a number is not necessarily expensive, but it does mean you cannot include it in an analysis like this one, and you will spend a sales call to learn what a competitor tells you on a web page in ten seconds.

09How to spend less without losing coverage

Five adjustments that reduce cost without reducing what you learn, in rough order of impact.

One, cut engines before you cut prompts. Prompt breadth is what finds gaps; engine breadth mostly confirms the same gap in more places. If your buyers concentrate in two or three assistants, paying for eleven is the largest avoidable line in your bill.

Two, check weekly rather than daily. On a credit model this is roughly a sevenfold reduction in consumption. Citation positions do move fast, as the 2025 swing in ChatGPT source weighting showed, but they do not move usefully fast at a daily cadence for most B2B categories, and DiscoveredLabs suggests evaluating strategy quarterly even while tracking weekly.

Three, run the baseline by hand first. Twenty prompts across three engines, recorded in a spreadsheet, costs nothing and tells you whether you need to monitor continuously at all. A meaningful share of teams discover their branded coverage is fine and their category coverage is the problem, which narrows what they need to buy.

Four, buy add-on prompts rather than the next tier. Where published, add-ons are frequently cheaper per unit than the tier jump. Otterly’s extra prompts at $99 per 100 work out near $0.99 each, cheaper per prompt than its own $189 tier.

Five, separate measurement from diagnosis. This is the structural point. These tools price the measurement, and measurement alone does not tell you why an engine favours a competitor. Since AI citation is heavily concentrated in a small set of community, review and editorial sources, watching those sources is often a cheaper and more actionable purchase than buying more prompts. We set out the evidence for that concentration in AI citation share benchmarks.

10Three budgets, three answers

Applying all of the above to the three situations most teams are actually in.

Scenario one: you do not yet know whether you have a problem. Budget zero. Run 20 prompts by hand across ChatGPT, Perplexity and Google AI Mode, then use AthenaHQ’s free Essential tier with its 300 credits across five engines to automate a second pass. If your branded coverage is strong and your category coverage is weak, you have found the shape of the problem without spending anything, and you now know which prompts matter.

Scenario two: seed-stage, real problem, tight budget. Roughly EUR 99 to $189 per month. Rankscale Pro if you want breadth and somebody will watch the credit burn, Otterly’s $189 tier if you want a number you can forecast and defend. At this stage prompt breadth beats engine breadth, so favour whichever gives you 100 prompts rather than whichever lists more engines.

Scenario three: funded, competitive category, need the answer to be defensible internally. $250 to $400 per month buys Scrunch at $250 or Profound at $399, both of which carry the enterprise reporting and compliance posture that survives a procurement review. At this budget, ask each vendor the itemisation question from the section above, because at $399 for 100 prompts you are paying roughly $3.99 per prompt and you are entitled to know what else that buys.

Across all three, the same discipline applies: write the prompt list first, price against that list rather than against an entry tier, and confirm the engine count the base price actually covers before signing anything.

11Frequently asked questions