What Do Profound Alternatives Actually Cost?

Search for Profound alternatives and page one hands you six listicles. Two of them rank a tool most practitioners have never heard of at number one. One recommends a $9 a month product as a serious replacement for a platform built on 1.5 billion real-user prompts.

Every one of them sorts on the same two columns: feature checkmarks and entry price.

We sell no platform. We run the measurement and the work behind it for clients, so the only question we care about is whether the thing you are about to buy can carry the decision you are buying it for. For this shortlist, that means converting every vendor to a unit none of them publishes.

What do Profound alternatives actually cost?

Normalised to cost per AI answer, the Profound alternatives range from $10.19 per thousand answers at Otterly Premium to $79.60 at Ahrefs Brand Radar, against Profound's own $44.33 on Growth and $66.00 on Starter. Every vendor in the bracket delivers exactly 30 answers per prompt, per engine, per month. You are buying breadth, not resolution.

That last sentence is the whole post.

You are not shopping for a cheaper Profound. You are shopping for a different sample of the same reality.

The bracket is not priced in a unit you can compare

Here is why no published comparison does this arithmetic: the vendors do not agree on what they are selling.

Profound sells answers, and it is the only one that says so out loud

Profound's pricing page lists Starter at $99 a month for one engine, 50 prompts and 1,500 monthly responses. Growth is $399 for three engines, 100 prompts and 9,000 responses.

That response figure is the number that governs reliability, and Profound is alone in printing it.

The response allowance turns out to be the daily run, written down

Check the arithmetic. Fifty prompts on one engine, refreshed daily, is 50 x 1 x 30 = 1,500. One hundred prompts on three engines is 100 x 3 x 30 = 9,000.

Both match the published allowance exactly. Profound is not selling you extra sampling on top of a daily refresh. It is selling you the daily refresh and reporting the total.

That identity is what makes the rest of the table possible. Once you know the formula reproduces the one vendor who publishes the answer, you can apply it to every competitor that publishes a refresh frequency instead.

Everyone else sells prompts, engines or checks, and lets you infer the rest

Otterly's pricing lists 15, 100 and 400 search prompts at $29, $189 and $489, on four engines, at daily tracking frequency. Semrush lists 25 custom prompts with daily AI rankings across four platforms at $99 per domain. Peec includes three of six engines on every self-serve tier and refreshes daily.

Ahrefs Brand Radar breaks the pattern entirely and sells 2,500 checks a month for $199, with overage at $0.020 per check.

Scrunch is the one row I left off the chart. Its own pricing page lists 350 custom prompts on the $250 tier, while third-party teardowns report the Core plan as 125 prompts where each engine counts separately, which works out to roughly 31 unique queries. Both cannot be describing the same product. When a vendor's unit is disputed by a factor of ten, no cost-per-answer figure is honest, and I would rather have a gap in the table than a number I cannot stand behind.

What every Profound alternatives list asks:

• •How many engines are included?
• •What does the entry tier cost?
• •Does it do sentiment and competitor tracking?
• •Is there an API and how many seats?

What a normalised comparison asks:

• •How many answers does each dollar actually buy?
• •How many of those answers land on any one prompt?
• •Does that count clear the threshold where rankings stop wobbling?
• •Can I buy more answers on the same prompt at any price?

Every list on page one answers the first four. The last four decide whether the number on the dashboard means anything.

6 things every Profound alternatives list gets wrong

None of these are defects in the products. Each one follows from ranking measurement tools by feature count when the constraint sits in the sampling.

Mistake #1: Comparing entry prices across vendors selling different quantities

Otterly Lite at $29 and Semrush at $99 look like a three-times price difference. Per answer they are $16.11 and $33.00 per thousand, so the real gap is closer to two. Otterly Lite also caps you at 15 prompts, which is one buying conversation rather than a prompt set.

Cheap per month and cheap per answer are different properties, and the listicles only ever report the first.

Mistake #2: Treating engine count as coverage when it multiplies your bill, not your depth

Adding an engine multiplies the answers you get, which looks like a bargain until you notice it does nothing for any individual prompt. Four engines on 15 prompts is 1,800 answers spread so thin that no single question gets a usable sample.

Engine breadth tells you where you stand across surfaces. It never tells you whether any one of those standings is stable.

Mistake #3: Assuming a cheaper vendor resamples less often

It does not. Every self-serve tier in this bracket that publishes a refresh frequency publishes the same one: daily. Otterly at $29 and Otterly at $489 both run once a day. Profound at $399 runs once a day.

The daily run is the industry default, and it is the reason the resolution column is a flat 30 from top to bottom of the table.

Mistake #4: Ignoring that 30 answers a month sits below the published stability floor

In July 2026, Ronald Sielinski published From Stochastic to Stable, a convergence framework for deciding when an AI visibility measurement has collected enough answers to be trusted. Across 30 platform-topic combinations on Gemini, SearchGPT and Perplexity, stable rankings required between 33 and 94 answers. Three of the 30 never stabilised at all, even after 125.

The paper is an unreviewed preprint and Sielinski says plainly that the exact figures will not transfer cleanly to other topics. The method transfers. The 33 does not.

Treat it as an order of magnitude and the conclusion still holds: 30 is the same size as the floor, which makes the reliability of every tier in this bracket a live question rather than a settled one.

Mistake #5: Recommending a switch as the fix for a number that barely moves

Our concluded CITE Index study ran 500 buyer prompts nightly through ChatGPT, Gemini and Google AI Mode for 63 days, collecting 90,132 answers across 10 consumer categories.

Across those 63 days the category leader flipped on only 18.7% of day pairs, and in four of the ten categories it never changed once. The average category leader appeared in 78.2% of its own category's answers. The full corpus sits in the final report.

That is incumbency, not instrumentation. A cheaper dashboard pointed at a standing that holds for weeks will produce a cheaper chart of the same result.

Mistake #6: Never mentioning that depth is unbuyable in this bracket

This is the one that costs the most, and I have not seen it written anywhere. Read every pricing page in the category and try to find a tier that offers more than one run per prompt per engine per day. There is not one.

You can buy more prompts. You can buy more engines. You cannot buy the same prompt sampled twice as often, at any price, from any self-serve vendor here.

Ahrefs is the closest thing to an exception, because its overage model prices the unit directly at $0.020 per check. Profound Enterprise is the other, because the response allowance is negotiable once you are in a quoted contract. Both routes require asking for something no pricing page offers.

Price buys breadth in this bracket. Nobody sells depth.

What Profound does that the cheaper alternatives do not

Fit is more useful to you than a verdict, and three things here are worth saying plainly.

The prompt-volume index is built on more than 1.5 billion real-user prompts, which means its volume data reflects questions people asked rather than questions a growth team imagined. A perfectly sampled answer to a prompt nobody types is still zero information, and this is the only dataset in the bracket that addresses it.

Engine breadth at the quoted tier reaches nine, against four or fewer everywhere else on the self-serve shelf. If your buyers are spread across Claude, Copilot, Meta AI and DeepSeek, the cheaper options do not reach them at any tier.

The research operation is real. Profound's ChatGPT Shopping teardown analysed 812,190 product cards across 201,137 prompt runs in a single week of June 2026. Commerce surfaces are barely instrumented anywhere else in this field.

Read what a vendor publishes about its own limits before you read what a competitor publishes about them.

Sizing a Profound replacement before you switch

The diagnostic half is done. Here is the sequence we run with clients before they move off any platform in this bracket.

Step 1: Write down the decision the dashboard is supposed to inform

Before you compare tiers, write one sentence naming the decision you will make differently based on what the tool reports. "Whether to fund review acquisition this quarter" is a decision. "Understanding our AI visibility" is not.

A tier that cannot resolve the difference you would act on is the wrong tier, whatever it costs per answer.

Step 2: Run your ten highest-intent prompts by hand across every engine

Open ChatGPT, Gemini, Google AI Mode, Perplexity, Copilot and Claude, and run the same ten shortlist-stage prompts your buyers ask. Record where you appear, which competitors appear instead, and every domain cited.

Two hours of this tells you which engines carry your category. It is the only part of the evaluation that samples your actual buyers rather than a vendor's panel.

Step 3: Convert every shortlisted tier to cost per answer before you compare

Take the prompt count, multiply by included engines, multiply by 30, and divide the monthly price by the result. Do it for the configuration you would actually run, with the add-on engines your step 2 findings say you need.

Most published comparisons put one vendor's entry price against another vendor's real configuration, which flatters exactly one of them.

Step 4: Establish your noise band before you set any threshold

Freeze your prompt set and run it for four to six weeks with no content or off-page changes, then record the spread. That spread is your category's noise band.

Our data suggests a single day's leader change is not a threshold in most categories. Without a band, a daily-refresh tool generates a weekly meeting about resampling, which we costed out in how many prompts are enough.

Step 5: Ask every vendor on the call whether depth is purchasable

This is the question that separates the shortlist. Ask each one: can I run the same prompt on the same engine more than once a day, and what does that cost?

Most will say no, and say it in a way that suggests nobody has asked before. The ones who say yes are selling you something the pricing page does not, and that is worth more than two extra engines.

Step 6: Fund the earned half from the same budget line

Whatever the new licence costs, hold back a matching share for the work that puts you inside other people's pages: earned mentions, comparison placements, review-site position, community presence.

In our corpus, four of the twelve most-cited domains were brand-owned. Reddit alone drew 14,698 citations and appeared in 13.6% of all 90,132 answers. Split the budget when you sign, not after the first flat quarter. That split is the entire reason a managed GEO agency sits next to tooling rather than inside it.

The field, by what each option actually constrains

Option	What it constrains	Right when
Stay on Profound	Cost per answer, at $44.33 per thousand on Growth. Depth is negotiable only at Enterprise	You need more than four engines, the prompt-volume index informs your roadmap, or commerce surfaces matter.
Otterly	Engine mix. Claude, AI Mode and Gemini are paid add-ons on top of the four included	Cost per answer is the binding constraint and your buyers sit on ChatGPT, Perplexity, Copilot or AI Overviews. Our read on Otterly covers the multi-country angle.
Peec AI	Three engines included from six on offer, on every self-serve tier	Your buyers cluster on three engines and you need unlimited seats. What Peec actually tracks prices the fourth engine.
Semrush AI Visibility	Prompt count. 25 daily prompts is one buying conversation	One domain, one core topic, and Semrush already in the stack.
Scrunch	Unit definition. Published prompt counts disagree by a factor of ten	You want seven platforms on an entry tier and will pin the unit down on the call. Our teardown covers the Sitecore split.
Ahrefs Brand Radar	Nothing, structurally. It is the only vendor pricing the unit that matters, at $0.020 per check	You want to buy depth on a narrow prompt set rather than breadth on a wide one, and you already pay for Ahrefs.
A managed program	Nothing, if scoped right. It costs a retainer	The measurement was never the bottleneck and nobody owns the weekly loop.

The rest of the field is mapped in our survey of GEO tooling for 2026, and the six jobs to score any of them against sit in the AI visibility platform buyer's guide.

FAQ

What are the best Profound alternatives?

The names that come up most are Peec AI, Otterly, Scrunch AI, Semrush AI Visibility and Ahrefs Brand Radar. Ranked by cost per answer from published limits, Otterly is cheapest at $10.19 to $16.11 per thousand, Peec sits at $21.11, Semrush at $33.00 and Ahrefs at $79.60, against Profound's $44.33 on Growth. Every one of them delivers 30 answers per prompt per engine per month, so the ranking tells you what breadth costs and nothing about which number you can trust.

How much does Profound cost?

Profound publishes two self-serve tiers and one quoted tier. Starter is $99 a month for one engine, 50 prompts and 1,500 monthly responses. Growth is $399 for three engines, 100 prompts and 9,000 responses. Enterprise is custom-quoted and adds up to nine engines, SSO, SOC 2 and API access. The response allowances work out to $66.00 and $44.33 per thousand answers. Confirm against a live quote, because published limits in this category move often.

Profound vs Peec: which should you buy?

They constrain different things. Peec includes three engines from six on every self-serve tier and charges $35 to $165 a month per additional model, so five engines on Pro costs $415 rather than the $245 headline. Profound Growth includes three engines at $399 and reaches nine at the quoted tier. Per answer Peec Starter is roughly half the cost of Profound Growth. If engine breadth beyond four decides your reporting, Peec cannot get you there on self-serve at any price, and that is the deciding difference rather than the monthly figure.

What are the best Peec AI alternatives?

The same bracket, viewed from the other end: Profound, Otterly, Scrunch, Semrush AI Visibility and Ahrefs Brand Radar. The comparison worth running is engine mix against cost per answer, because Peec's constraint is the three-engine cap rather than its price. If the engines you need are inside Peec's included three, it is among the better value in the field. If you need a fourth and fifth, price the add-ons into the total before you compare it against anything.

Which LLM visibility tools let you sample the same prompt more than once a day?

None of the self-serve tiers we reviewed. Every vendor publishing a refresh frequency in this bracket publishes daily, which caps you at roughly 30 answers per prompt per engine per month regardless of what you pay. Two routes exist around it: Ahrefs Brand Radar sells checks directly with overage at $0.020 each, and Profound's response allowance is negotiable inside an Enterprise agreement. Ask for it explicitly, because no pricing page offers it.

The bottom line

Every tool on your Profound alternatives shortlist is a better or worse deal on breadth. Not one of them is a better deal on the thing that decides whether the number holds up, because not one of them sells it.

Do step 3 before you take a demo. Convert the configuration you would actually run into cost per answer, and you will usually find the ranking on page one inverts. Then ask step 5 on the call and watch which vendors have thought about it.

Then go do the work no licence covers. Nothing in the software writes the answer block, fixes the passage the model could not extract, or earns the third-party mention that puts you in the source pool. An AI visibility audit will show you which half your gap sits in before you sign for another year of anything.