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Marketing · 9 min read

Advertising on ChatGPT: what we learned from an early field test

A three-week test of OpenAI's ChatGPT ads beta for a B2B WordPress product: how the platform works, what it costs, the results we measured, and who it's actually for.

August 20, 2026

I run marketing at GravityKit, a B2B WordPress plugin company. When OpenAI opened its ChatGPT ads beta to advertisers, we decided to run a proper test: three weeks in late July and August, a capped budget, two ad groups pointed at our best landing pages, and full conversion tracking wired up before launch.

The headline results: clicks were cheap and plentiful, engagement was near zero, and we measured no conversions or key events at all. We paused the campaign early.

Almost everything written about ChatGPT ads so far is either agency content marketing or secondhand news coverage, so this post is the account I wanted to read before we spent the money: how the platform works as of August 2026, what it costs, the results we saw, the rough edges you only find by spending, and who should (and shouldn’t) test it.

How ChatGPT ads work

If you’ve run Google or Meta campaigns, the structure is familiar: campaign, ad groups, ads. You pick an objective per campaign (Views billed on CPM, Clicks billed on CPC, or, more recently, conversion-optimized campaigns), set a daily budget and max bid, choose countries, and submit ads for review. Under the hood, OpenAI’s advertiser documentation describes a relevance-weighted, second-price auction. Ads render as clearly labeled sponsored units beneath the assistant’s answer.

The genuinely new part is targeting. There are no keywords. Each ad group gets a single context hint: one full sentence describing the conversations you want to appear in, like “a user is asking how to display form submissions on their WordPress website.” ChatGPT matches your ads to conversations using that hint, your ad copy, and your landing page. Measuring anything beyond clicks means installing OpenAI’s measurement pixel on your site first.

Two other facts shape everything else:

  1. Only free-tier users see ads. OpenAI’s own FAQ is explicit: ads may appear for Free and Go plans, while Plus, Pro, Business, Enterprise, and Edu accounts never see them. Keep this in mind whenever someone quotes ChatGPT’s total user numbers at you.
  2. The platform is moving fast. Features have been shipping monthly since the beta opened in early 2026. Some of the limitations below may be fixed by the time you read this, which is why I’ve dated everything.

There’s also an Advertiser API covering campaigns, ad groups, ads, and reporting. It’s useful, and we ended up needing it for reasons we didn’t expect (more below), but it has quirks: historical per-ad numbers can restate between pulls, insights requests silently cap at 20 daily buckets (ask for a longer window and your earliest days just vanish from the response), and you’ll want to script against it with curl since the default clients of some HTTP libraries get blocked at the edge.

What ChatGPT ads cost

Our setup: one campaign, Clicks objective, $25 a day (currently the minimum daily budget), a fixed $3.00 max CPC (the bottom of OpenAI’s recommended $3 to $5 starting range), targeting the US, UK, Canada, Australia, and New Zealand. Two ad groups with three ads each, one context hint per group, pointing at two different use-case landing pages.

What we actually paid over three weeks: about $550 for roughly 12,800 impressions, a 1.7 percent CTR, and an average CPC of $2.57. That CTR is healthy for a placement that sits underneath an answer the user already got.

Two pricing observations worth knowing:

The results

Front-end metrics were fine. Back-end was a flat zero.

Roughly 150 tracked users from paid ChatGPT traffic produced no product page views, no checkout starts, and no purchases. Not weak numbers: zero. Average engagement for most ads sat far below what the same landing pages see from search traffic. We killed the campaign on day 20 of a planned 34.

Here’s the same window (July 28 to August 17) in GA4, side by side with our other channels:

Traffic sourceAvg engaged time per sessionPages per sessionKey events per 100 sessions
ChatGPT ads (paid)5 s10
ChatGPT organic referrals40 s3.513
Google Ads (search)65 s4.87
Organic search51 s3.65

Could the tracking have been broken? No: during the test, one organic (unpaid) ChatGPT referral converted into a purchase, flowing cleanly through the same measurement pipeline. The plumbing worked. The paid traffic just didn’t have intent.

Our results rhyme with the few other first-person accounts out there. SE Ranking ran a bigger test and reported plenty of clicks but very few signups, and Omni Lab’s write-up on ChatGPT ads for B2B found the same structural problems we did, including a poll where 74 percent of their SaaS-marketer audience was on a paid, ad-free ChatGPT plan.

One more pattern worth flagging: you can’t control devices. The only targeting lever the platform offers is geography (country, region, or DMA), so campaigns serve wherever ChatGPT runs, mobile included, with no way to turn it off. About 70 percent of our paid sessions came from mobile. My hunch going in was that the cheap clicks were mostly mobile fat-fingers, and the mis-tap signature is real (lots of three-to-seven-second sessions), but the data was less kind than that: desktop sessions were just as shallow. Low intent, not just loose thumbs.

The targeting black box

There’s no conversation-level reporting. No equivalent of a search terms report. No way to check whether your ad surfaced in a genuinely relevant conversation or something loosely adjacent. You write your hint, the system matches, and you read aggregate numbers. You’re trusting the targeting entirely.

The closest we got to visibility was forensic. Early in the test, one ad group was soaking up 89 percent of impressions while its twin starved. The cause turned out to be a platform bug: the UI had split a comma-containing context hint into one-word fragments, so an ad group was effectively targeting the word “show.” We caught it by pulling the ad group config through the API, not through anything the reporting surfaced. The bug came back once after we fixed it, so we ended up re-verifying hints via API after every UI edit.

That incident proved hints really do steer delivery. But we only learned it because something broke. In normal operation you have no idea what contexts you’re buying, and there’s no negative targeting to exclude the ones you’d never want.

Other rough edges

A few more things from the trenches, all as of August 2026:

Is advertising on ChatGPT worth it in 2026?

We deemed it not to be worth it for us, and paused the campaign early. That’s a verdict on the channel today, not forever: the platform is shipping fast, and the reasons it didn’t work for us are structural rather than creative:

Where it may have a better chance of working: consumer products with broad appeal, impulse-friendly price points, and audiences that actually use free ChatGPT. If someone asks ChatGPT for dinner ideas and you sell meal kits, the logic is sound.

And the math changes if OpenAI ships some combination of paid-tier inventory, conversation-level reporting, negative targeting, working conversion optimization, and lower retargeting thresholds. Given the current shipping pace, we’d re-evaluate in six months rather than write the channel off.

If you test it anyway

Five things we’d do differently, or did and would repeat:

  1. Install the measurement pixel first and verify it’s firing correctly (fire a test event, confirm it lands in Ads Manager) before spending a dollar.
  2. Write context hints as single full sentences, never comma-separated lists, and verify them through the API after every edit.
  3. UTM-tag everything and reconcile platform clicks against your analytics from day one. Expect a gap.
  4. Judge the test on engagement and pipeline, not clicks. The clicks will look cheap. That’s not the same as good.
  5. Cap the budget and set an end date before you start.

You can buy the placement, but not the answer

The bigger lesson isn’t about this ad platform. Paid placement under an AI answer competes with the answer itself, and the answer already satisfied the user. The durable win is being in the answer: cited, recommended, linked. That’s earned through the kind of work I’ve written about in the 7 pillars of GEO, and you can measure it today by tracking AI referral traffic. Our one conversion from ChatGPT during this whole test came from exactly that: an organic recommendation, not a paid unit.

Ads on ChatGPT will mature. The mid-funnel shift I described in AI ate the mid-funnel guarantees the ad dollars will follow the attention. But right now, if you have budget to spend on AI channels and a technical audience, I’d put it into becoming the answer, not renting the space below it.

Have you run your own test? I’d genuinely like to compare notes, especially if your results diverge from mine.

Casey Burridge

Cowritten by Casey & Jarvis 🤖

Casey Burridge

Strategic Growth & Operations Manager at GravityKit. Full-stack marketer, WordPress consultant, and AI-first ops builder. About · Hire me · LinkedIn