ChatGPT Ads
Creative & Intent
The ad has to read like the natural next step after the answer. That is a writing problem before it is a media problem.
Message match is where the performance is
Someone who just read a balanced comparison of four vendors is in a very specific state of mind. They have context, they have criteria, and they are one decision away. An ad written for a cold audience wastes that moment entirely.
We write per question type. A pricing question gets a different promise than an alternatives question, and both get a landing page that picks up exactly where the answer left off instead of restarting the pitch.
What we produce
- 01
Copy variants by question type
Separate lines for best, pricing, alternatives and comparison prompts, each matched to the mindset behind it.
- 02
Offer framing
How the offer is presented to someone comparing options: what to lead with, what to prove, what to leave out.
- 03
Landing page continuity
Pages that answer the same question the user asked, with the proof and call to action a decision-stage visitor needs.
- 04
Trust and credibility signals
The proof points, differentiation and social proof that shorten the distance between click and enquiry.
- 05
Structured testing
Variations tested by intent type, so improvements are based on how people decide rather than on gut feel.
Creative questions
Can we reuse our existing search ad copy?
As raw material, yes. But copy written for a ten-result page tends to shout. Conversational placements reward a calmer, more specific tone that reads as a continuation of the answer.
Do you build the landing pages?
We specify and write them, and we can build them or hand a clear brief to your team. What matters is that the page continues the conversation rather than restarting it.
How many variants do you run?
Enough to learn without splitting the data too thin. In practice that usually means two to three angles per question type at the start.