Turn one B2B campaign message into controlled creative hypotheses, ad variants, QA gates, launch notes, and performance learnings your next test can reuse.
Create a paid social creative testing system with a hypothesis matrix, source pack, approved variants, launch matrix, and performance learning loop.
Quick view
Check the audience, core tools, and access before you start the detailed steps.
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Core tools
5 tools used across the workflow.
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Why this works
Most AI ad creative workflows create volume without learning. This workflow starts by deciding what buyer belief each ad is testing, then keeps the audience, offer, proof, and landing page alignment visible through production and launch. The result is a creative system that improves with every test instead of a folder of disconnected images.
Expected results
Creative variants
12-24 QA-ready variants
The workflow creates a practical batch across a small number of controlled hypotheses, with each variant tied to a concept, proof source, and launch record.
Creative quality
Approved, revised, or rejected
The QA gate forces every variant through claim accuracy, brand fit, mobile readability, CTA clarity, and landing-page alignment checks before launch.
Learning output
1 hypothesis-level readout
Performance is reviewed by buyer belief and creative angle, so the team learns which message directions deserve the next round of spend.
Time saved
6-12 hours per cycle
Preview the open steps, then unlock the remaining implementation details and prompts.
Reusable Airtable fields, Claude prompts, Canva templates, naming rules, and readout structure reduce the strategy and production work required for each new campaign.
Step-by-step workflow
The first 3 steps are open. Pro unlocks the remaining steps, copy-paste prompts, pro tips, tool-by-tool setup guidance, and implementation details.
30-45 min
30-45 min
Start in Airtable and create one control record for the campaign before generating any creative. Add fields for campaign name, target audience, buyer problem, offer, approved proof point, landing page, CTA, primary test variable, variables to keep fixed, review owner, and approval status. Write the campaign message as one sentence using this structure: audience, problem, offer, proof, and desired action. Mark the primary test variable as message angle, visual format, offer framing, or proof type so the team knows what the test is actually measuring. Before moving on, have the campaign owner approve the message and reject any version that tries to test multiple audiences, offers, and creative formats at once.
An approved campaign control record with the message, test variable, fixed variables, owner, and approval status.
If the one-sentence message feels hard to write, that is usually a strategy problem, not a copy problem. Fix it before you create ten versions of the wrong idea.
45-60 min
45-60 min
Create a second Airtable table for the source material every creative variant is allowed to use. Add fields for approved claim, proof source, customer example, screenshot link, product area, banned wording, required disclaimer, landing page promise, brand rule, and claim approval owner. Include prior ad performance if you have it, but keep it tied to the original audience, offer, and channel so old results are not overgeneralized. Add a view called Needs approval that only shows claims without approval status and a view called Ready for creative that only shows claims approved for use. Do not let Claude, Canva, or AdCreative.ai invent proof that is not already in this table.
A campaign source pack with approved claims, proof sources, brand constraints, banned wording, and review views.
The source pack protects you from the most common AI ad mistake: beautiful creative wrapped around a claim sales, legal, or product cannot defend.
45-60 min
45-60 min
Use Claude to turn the approved campaign message into six to eight creative hypotheses, then paste the output into an Airtable hypothesis table. Create fields for hypothesis name, buyer belief, creative angle, required proof, visual direction, CTA, expected behavior, primary metric, risk, and review status. Each hypothesis should test a real belief, such as whether buyers respond more to risk reduction, speed, competitive pressure, peer proof, cost control, or missed-opportunity framing. Reject hypotheses that are only copy variations, because they will not teach the team anything meaningful. QA the set by checking that every hypothesis uses the same audience, offer, and landing page unless the campaign is explicitly designed to test one of those variables.
A QA-reviewed creative hypothesis matrix with buyer beliefs, angles, proof requirements, metrics, and risks.
A good hypothesis should be falsifiable. If a bad result would not tell you what to stop doing, the hypothesis is too vague.
Pro workflow preview
Previewing 3 of 10 steps
Get the remaining 7 steps, copy-paste prompts, pro tips, tool-by-tool setup guidance, and ongoing workflow and prompt releases.
$9/month
Create paid social creative hypotheses from this B2B campaign message.
Campaign message:
{{campaign_message}}
Target audience:
{{target_audience}}
Offer:
{{offer}}
Approved proof points:
{{approved_proof_points}}
Landing page promise:
{{landing_page_promise}}
Prior performance notes:
{{prior_performance_notes}}
Rules:
- Keep audience, offer, and landing page fixed unless I explicitly say otherwise
- Do not invent claims or proof
- Do not create slight wording variations as separate hypotheses
- Make each hypothesis falsifiable
Create 6-8 hypotheses. For each include:
1. Hypothesis name
2. Buyer belief being tested
3. Creative angle
4. Required proof
5. Visual direction
6. CTA
7. Expected behavior if the hypothesis is true
8. Primary metric
9. Risk or weakness
10. Reject/revise notes if the hypothesis is not testableRelated workflows
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