OpenAI Ads

The goal of everything here: as many clicks and conversions per unit of spend as possible, and from those, leads that turn into business. Reach without conversion is not success.

Read first

• references/platform-facts.md — every hard limit and rule
• references/misinformation.md — always read before quoting a figure or a feature. A lot of false information about this platform is in circulation.
• references/benchmarks.md — sufficiency thresholds and your own measured values

Do not load all three at once. Copy work needs platform-facts; assessments add benchmarks.

The one rule that shapes everything

There is no reporting per context_hint. The API accepts up to 2000 hints per ad group but never reports which of them produced a conversion.

That determines how every campaign is cut:

The ad group is the smallest unit of measurement. So: few hints per group, tightly scoped by theme, and more groups instead.

A group with 200 hints is a black box — it may perform, but you never learn why, and you cannot repeat it. Five groups with 10 to 20 hints each produce usable signal.

Guideline: 10 to 25 hints per group. Warn above 50.

Routing

Build order

The sequence matters because each step depends on the previous one:

1. get_account — currency, timezone, review.status. If rejected with missing_favicon, fix the account first.
2. check_feature_access — what is enabled? This API answers 403, and sometimes 404, when something is gated.
3. Conversion measurement before the first campaign. Without it you cannot switch to conversion bidding later — bidding_type is immutable.
4. Check the landing page — reachable for crawlers, no redirect, favicon present.
5. Create the campaign paused, then the ad group, then the image, then the ad.
6. preview_ad and look at it.
7. Only then activate, one thing at a time.

Structure

• One campaign per goal and bidding type. bidding_type cannot be changed, so anyone planning to move to conversion optimisation later will need a new campaign anyway.
• One ad group per intent. Not per product, not per audience. Intent determines which phrasing lands.
• Two or three ads per group, using different angles rather than reworded versions of the same claim. Only then is the comparison meaningful.

Assessing

Run the sufficiency check from references/benchmarks.md before quoting any number. If the data is too thin, output no score — state what is missing and how long to keep measuring.

Assess against the maximum tolerable CPA derived from the business model, not against industry figures. There are none for this platform.

Every recommendation needs four things

Without these it is a finding, not a recommendation:

1. Observation — what it rests on, with a number
2. Dependency — what has to happen first
3. Falsification — how would you know it did not work?
4. Leading indicator — what moves first, without re-running the analysis

Point 3 matters most. Anyone who cannot say how they would notice being wrong is recommending on a hunch, and here that spends real budget.

When things go wrong

What this platform cannot do

Do not look for, suggest or claim: keyword bidding, match types, keyword planner, search volume, radius targeting, personalised ads in the EEA, a sandbox, official benchmarks, a Python SDK.

Details and reasoning in references/misinformation.md.