Why early ChatGPT Ads results are hard to benchmark
Brooke Osmundson compares early public accounts of ChatGPT advertising and explains why they do not yet provide a reliable universal benchmark. Advertisers are testing different offers, audiences and measurement setups, while reporting and targeting differ from established search campaigns. Read this before using a quoted CPC or success story in a forecast. The article is most useful for framing a test around your own lead quality and commercial outcomes, and for separating a recommended bid from an observed acquisition cost.
Search Engine Journal · Published
Why make time for it?
Useful before a stakeholder turns one early advertiser result into a target for your account.
What to look for
- Separate bid recommendations from observed costs and outcomes.
- Connect a test to CRM quality rather than clicks alone.
Keep in mind
The article synthesises early public tests. Their results and platform capabilities are time-specific and are not representative market benchmarks.
Take this question into the article
Which downstream outcome would make your own ChatGPT Ads test worthwhile?
The people behind the article
Explore their work and recorded contributions on PMC.
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Read the full argument.
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Read the full articleReading notes reviewed 30 Sept 2026. The publication date above belongs to the original source.