Run both. Keep Google Ads doing what it already does, and put a small, deliberate test into ChatGPT Ads beside it, never instead of it. Google sells you a keyword; ChatGPT sells you a conversation, and you cannot buy the same certainty. The comparison below goes field by field.
Every guide to ChatGPT Ads quotes the same number: three to five dollars a click. That number is not a price. It is the maximum bid OpenAI suggests you start at, published in its own help documentation, and repeating it as though it were a cost is the single most common mistake in the coverage of this channel.
Here's the thing. The interesting difference between these two platforms is not price at all. It is how much of the buying decision you are allowed to make yourself.
| Google Ads | ChatGPT Ads | |
|---|---|---|
| What you buy | A keyword, with a match type you choose | Relevance to a conversation, described in free text |
| Targeting controls | Keywords, audiences, demographics, location, device, schedule | Location only, at campaign level |
| Negatives | Negative keyword lists, exact and phrase | One free-form exclusion_hints field |
| Headline length | 30 characters × up to 15 headlines | 50 characters, one |
| Body length | 90 characters × up to 4 descriptions | 100 characters, one |
| Where you can advertise | Effectively worldwide | 7 countries |
| Query-level reporting | Search terms report | None |
| Maturity | 25 years | Public beta since May 2026 |
The difference that decides everything else
On Google Ads you tell the platform what to match. You pick the words, you pick how loosely they may be interpreted, and you tell it what never to match. That control is the whole product, and every skill an advertiser builds sits on top of it.
ChatGPT Ads does not work that way, and the gap is wider than most write-ups admit.
Read OpenAI's campaign targeting documentation and you find exactly one targeting field on a campaign: targeting.locations.include, which takes a country, a region, or a designated market area. That is the complete list. Leave it empty and the campaign runs everywhere it is allowed to run.
One level down, at the ad group, you get a field called context_hints — a free-text list of topics and phrases describing when your product might be useful. It looks like a keyword list. It is not one. OpenAI's own wording is worth quoting exactly, because it is the sentence the rest of this page hangs on:
These hints help guide ad matching, but they are not exact-match keywords and do not guarantee delivery in specific conversations.
You can supply up to two thousand of them. You still cannot make one fire.
Selection is a relevance-weighted, second-price auction that reads the conversation's context and intent alongside your title, your body copy, and your landing page. Translation: the model decides whether you are relevant, and the strongest lever you own is not a bid. It is how legibly your offer is written.
So what does that mean for you? Two things. A tight, genuinely relevant ad on a modest bid can beat a vague one bidding higher, which is unusually good news for small budgets. And the discipline that makes Google accounts profitable — ruthless exclusion — has almost nothing to grip.
What you can actually control
| Control | Google Ads | ChatGPT Ads |
|---|---|---|
| Match a specific query | Yes, exact match | No |
| Block a specific query | Yes, negative keywords | Only a free-form hint list |
| See which queries you paid for | Yes | No |
| Target by age, gender, income | Yes | No |
| Target by location | Yes | Yes — country, region, DMA |
| Day and hour scheduling | Yes | Campaign start and end only |
| Change bidding model mid-flight | Yes | No — fixed at creation |
| Pay per conversion signal | Yes, target CPA | Yes, conversion-optimized bidding since June 2026 |
That third row is the one to sit with. On Google, the search terms report is where the money is found. I once got access to a business-to-business fintech account running on autopilot with high-intent keywords and the wrong match modifiers, quietly pulling in consumer traffic nobody had excluded. Roughly eighty per cent of the budget was going to people who were never going to buy. The fix was obvious the moment I opened the search terms — and afterwards the company had to hire salespeople to keep up.
There is a way around it, and it is the first thing I would tell anyone running this channel. If you cannot see the query, build the report from the other end. Split your context_hints across separate ad groups, point each ad group at its own landing page, and let the destination do the reporting for you.
You never learn the exact wording. You do learn which conversation was worth paying for — and that is the half of a search terms report that actually changes a decision.
What a click actually costs
OpenAI recommends starting at a maximum bid of three to five US dollars per click, and sets the default maximum for impression buying at sixty dollars per thousand. Both figures come from OpenAI's own help documentation.
Those are ceilings you set, not prices you pay. In a second-price auction you pay what it takes to beat the next advertiser, which on a young platform with thin competition is often well under your maximum. The honest answer is that nobody outside the platform can tell you your number, because it depends on your category, your geography, and how relevant your ad reads.
What I can tell you is what we see. Across the local businesses I work with — medical clinics, automotive, retail, and high-billable professional services — cost per lead usually lands somewhere between thirty and a hundred and fifty dollars. I know that is a wide range. It is wide because those are genuinely different businesses, and any narrower number would be dishonest. We publish what we actually pay for ChatGPT clicks, by vertical.
One more thing worth knowing about budgets: the API will accept a campaign lifetime spend limit of one dollar. There is no meaningful floor. Whatever you have been told about minimum spend on this channel, the platform itself does not enforce one.
What you can measure
Ads Manager reporting currently covers impressions, clicks, spend, click-through rate, average cost per click, average cost per thousand impressions, and conversions. That is the whole list.
Conversions come through a measurement pixel or a server-to-server conversions application programming interface, the same shape as Meta's. Static tracking parameters survive the click, so if you tag your landing page URLs the traffic shows up in the analytics you already run.
Compared with Google, you are giving up the query view and the audience view. You are keeping the thing that actually matters, which is whether a click turned into a customer. If your conversion tracking is not already trustworthy, fix that before you spend a dollar here — a channel you cannot measure at query level is a channel you must measure at outcome level, or not run at all.
So where does the first $500 go?
Alongside, not instead. That is the whole answer.
Budget is a variable, not a number. A fixed monthly figure is a planning fiction; what should actually move your spending is seasonality, your capacity to fulfil the work, and how many buyers are genuinely in the market this month. So the question is never "should I move money from Google to ChatGPT." It is "can I afford a small, honest experiment while the channel that already produces customers keeps producing them."
Here is the one I can point at. We ran ChatGPT Ads alongside Google for an automotive client, sized to be readable rather than to look serious. It took one to two weeks before the numbers said anything I would trust. When they did, we kept it running and moved more budget into it.
One test in one vertical is not a law. It is one honest data point, which is one more than most of the pages you will read on this can offer.
Work through it in this order.
- Is your proven channel dialled in? If your Google account still has obvious waste in it, that is where the next five hundred dollars earns the most. Fix the leak before you drill a new hole.
- Can you measure an outcome? No working conversion tracking, no test. You would be buying traffic you cannot judge.
- Are you in one of the seven countries? Ads Manager is currently available to advertisers in Australia, Canada, Japan, Korea, New Zealand, the United Kingdom, and the United States.
- Is your category allowed? Several are not yet, and some of the biggest small-business categories are among them. Check the restricted list first.
- Then start small and move quickly. Size the test to produce a readable result, not to look serious. Scale what works, on evidence, even when that feels uncomfortably slow.
When ChatGPT Ads is the wrong call
I would not run it yet if any of these are true.
- Your buyers are in a hurry and nearby. Someone searching for an emergency plumber is not workshopping the decision with an assistant. Local search and Local Services Ads still win that moment.
- You have no conversion tracking. Covered above, and worth repeating, because it is the most common reason a test produces nothing but an invoice.
- Your category is restricted. Healthcare, financial services, and legal services are gated behind manual approval right now, and several categories are disallowed outright. I have one sitting in manual approval as I write this, submitted recently enough that I honestly cannot tell you yet whether the answer comes back in days or in weeks. Nobody publishes that number, me included. So start the approval before you plan the campaign around it.
- Nobody is watching the account. Autopilot is how ad budgets die. That is true on every platform, and it is truer on one where the negative controls are a suggestion.
None of that makes it a bad channel. It makes it an early one. Buyers are arriving faster than advertisers, which is exactly the shape of a real first-mover advantage — but only for people who bring the same discipline they would bring to search. New channel, old rules.
Common questions
Is ChatGPT Ads cheaper than Google Ads? Nobody can answer that for your business from public data, and anyone quoting the three-to-five-dollar figure as a cost is quoting a bid recommendation. What is true is that a young auction has fewer bidders in it, and that relevance weighting rewards a well-written ad more than a large budget.
Can I use my Google Ads keyword list? Not directly. context_hints accepts topics and phrases, but they are not matched exactly and they do not guarantee delivery. Your keyword list is useful as raw material for describing when you are relevant, not as a targeting import. If you are building that Google list in the first place, the prompts I use for it — and the ways each one fails — are in ten ChatGPT prompts for Google Ads.
Do ChatGPT ads show to everyone? No. OpenAI does not show ads to users on Plus, Pro, or any Business plan, nor to users it knows or predicts to be under eighteen.
Should I move my Google budget across? No. Keep the channel that produces customers producing customers, and fund the test separately.
What happens if I pick the wrong bidding model? You rebuild the campaign. bidding_type cannot be changed after a campaign is created, and I met that field the hard way on the first campaign I built here — wrong bidding model, no way to change it, so I tore the campaign down and rebuilt it before any real budget had gone through. The rebuild took under an hour. The cost is not the rebuilding. It is finding out a field is frozen after you have already made every other decision around it. There are a few more like it in the setup walkthrough.
Run both, without building it twice
Bytown builds the campaign once and pushes platform-specific versions to Google, Meta, LinkedIn and ChatGPT. You approve every campaign before a dollar moves.
Generate a free campaign Or read how ChatGPT Ads work for small business.