What ChatGPT Ads Cost: CPC and CPA

How this was compiled

The figures come from Bytown's own advertiser reporting across the ChatGPT Ads accounts we manage. They were hand-compiled from that reporting, not exported through a platform integration — no account has been connected through Bytown's ChatGPT Ads connector, so nothing here synced automatically. Somebody read the accounts and typed the numbers into a sheet.

Every rate is computed from summed raw counts, never averaged from per-account rates:

• CPC, cost per click — total spend divided by total clicks.
• CPM, cost per thousand impressions — total spend divided by total impressions, times 1,000. What it costs to be seen, whether or not anyone clicks.
• CTR, click-through rate — total clicks divided by total impressions.
• CVR, conversion rate — total conversions divided by total clicks.
• CPA, cost per conversion — total spend divided by total conversions. Also called cost per acquisition.

That distinction matters more than it sounds. Averaging the rate of a small test account against the rate of one spending 5 times as much gives the 2 equal weight, and produces a number that describes no advertiser at all.

Aggregation is by vertical, with no client names and no account-level figures. Where a vertical has few accounts, the account count sits in the table next to it rather than being hidden — you can see exactly how thin any row is and discount it accordingly.

Nothing is suppressed: every vertical we have data for is in the table, including the ones with 2 accounts behind them.

On the restricted categories. Several verticals here — dental, elective healthcare, med spa, legal, B2B fintech — sit in categories OpenAI's ad policies put under review rather than open by default, and most of them carry their own regulator on top (check yours).

Those accounts run on a mix of the 2 routes the policy allows, account by account: some as approved advertisers, some advertising an offer that is not in the regulated class to begin with. We are not attributing a route to any particular vertical, because doing so would identify clients.

If you are in one of these categories, read the 2 routes through before reading the numbers — which route applies to you changes what these figures mean for your own account.

What this is not: an industry benchmark. It is 1 agency's book of business, and the verticals in it are the verticals our clients happen to work in.

A vertical backed by 2 accounts tells you what those 2 accounts paid. It does not tell you what the category costs.

What the numbers say

4 things in the charts above are worth stating plainly.

The bid is not the price. The $3 to $5 maximum bid OpenAI recommends is a ceiling you set.

Simply put:

What you actually pay is decided by a relevance-weighted second-price auction, so it usually settles below that ceiling — and our blended cost per click lands under the bottom of the recommended range. Budget from the recommended bid and you will over-plan your click costs and under-plan everything downstream.

The blended figure is the least useful number on this page. Here is why.

A 9-fold spread between the cheapest and dearest vertical means the average describes almost nobody. What a click costs you depends far more on what you sell than on how well you run the account.

Bottom line?

Read your own row, not the total line.

The click price understates how different these verticals are. The slope chart ranks the same verticals twice and the ordering barely changes — expensive clicks stay expensive. What changes is the scale:

• Cost per click spans roughly 9 times from cheapest to dearest.
• Cost per conversion spans nearly 29 times, from $12 to $349.

Low click-through rates and low conversion rates tend to arrive together, so the gap compounds. Budget from the conversion column, not the click column.

Impression pricing runs the other way. The verticals with the highest CPM are frequently the ones with the lowest cost per click, because a high click-through rate spreads the same impression cost over more clicks. Compare the CPM and CTR charts and the inversion is easy to see:

• Elective healthcare buys the dearest impressions on the page, at $187.86 per thousand, yet sits mid-table on cost per click.
• Non-profit buys the cheapest, at $22.56, and ends up with the cheapest clicks and the cheapest conversions as well.
• Landscaping converts best of anything here — an 8.52% conversion rate against B2B fintech's 1.73%.

If you are buying on an impression basis, expect the vertical ordering to be close to inverted.

Reading the month-over-month line honestly

The trend chart plots 2 series, and the difference between them is the methodological point.

Accounts join mid-window. An account that started in June contributes to June and July but not to May, so a month-over-month line drawn across all accounts partly measures who was in the sample that month rather than what prices did. That is the faint line.

The solid line is a fixed cohort — only the accounts present in every month of the window. It is a smaller sample and a slower-moving one, and it is the only line here that supports a sentence beginning "costs rose" or "costs fell".

This edition is a clean example of why that matters:

• All 42 accounts: cost per click falls from $2.68 to $2.45 across the window — a 9% decline you could reasonably write up as the auction getting cheaper.
• The 23-account cohort present every month: $2.68 to $2.67. Which is to say it did not move.

Here's what it means.

The apparent decline is almost entirely newer, cheaper-vertical accounts entering the sample. Nothing got cheaper for anyone already running.

We publish both lines because publishing only the flattering one is how benchmark diaries stop being worth reading.

Against Google and Meta in the same verticals

The comparison people actually want is against what they already run, so here is the honest version rather than a table that implies more precision than exists.

Across local businesses — clinics, automotive, retail, high-billable professional services — I have generally seen cost per lead land somewhere between $30 and $150 on established search and social channels. That is a field observation from years of running those accounts, not an industry average, and the range is wide because the businesses are different.

Set that against the cost-per-conversion column here and the read is straightforward: for several consumer-facing local verticals, ChatGPT Ads is currently landing inside or below that band, and for business-to-business verticals it is landing well above it.

That gap is what you would expect from a channel where the auction is still thin in some categories and crowded in none.

Why does this matter?

It is also the kind of gap that closes. The reason to publish monthly is to catch the month it does.

For the full side-by-side on how the 2 channels differ structurally — conversational context against keyword intent, and what that does to measurement — see ChatGPT Ads vs Google Ads.

What this does not cover

Nothing here covers creative performance, because the sample is not large enough to say anything defensible about it yet — what the evidence actually says about ad creative is where that question is answered from published research instead.

Nor does it break out by geography — every account is North American, and the location targeting available on the platform is coarse enough that a city-level read would be invented rather than measured.

If you are in a restricted category, the route in matters more than the benchmark does — start with restricted industries on ChatGPT Ads, then the 2 routes through.

How this gets updated

New figures land monthly, recomputed from the same source and by the same method, with the sample size restated each time. When the sample changes materially — a vertical crossing into a meaningful account count, or a category opening up — that gets noted rather than absorbed silently into a revised average.

So what does that mean for you?

If you want to run the channel yourself, the field-by-field setup walkthrough is how to advertise on ChatGPT, and the overview of what the channel is and who can buy it sits on ChatGPT Ads for small business.

FAQ

Tomas Kolafa

Founder, Bytown

14+ years running paid acquisition, managing $85M+ in ad budgets — co-founded the ad agency Growth Media, led marketing ($0–50M) at RVezy.com. I’ve spent the budgets, run the campaigns, and read the reports.