5.1 — Ad Copywriting Fundamentals
Why most ads underperform — and the fix
Most small business ads fail for the same reason: they describe the product rather than speak to the problem
Most small business ads fail for the same reason: they describe the product rather than speak to the problem. This lesson covers the core principles of direct-response copywriting and how to apply them with AI — PAS, AIDA, and the before/after/bridge framework.
Think of a product or service you want to advertise. Ask AI: 'Write 3 versions of a Facebook ad for [product]. Use three different frameworks: PAS (Problem-Agitate-Solution), AIDA (Attention-Interest-Desire-Action), and Before/After/Bridge. Keep each under 150 words.'
Pay attention to how AI structures its response. Is it giving you something genuinely useful, or something generic? The difference is almost always in the specificity of your prompt — the more context you give, the better the output.
Applying this in practice
The real skill here isn't getting AI to produce something — it's knowing when the output is good enough to use and when it needs refinement. Review everything AI produces through the lens of your specific audience. If it could have been written for anyone, it needs more work.
AI handles the first 80% — structure, vocabulary, volume. You provide the remaining 20% — your specific audience insight, your brand voice, your judgment about what will land. Neither alone produces great marketing.
5.2 — Google and Search Ads
Headlines, descriptions, and keyword thinking
Search ads are intent-based — your customer is already looking for what you offer
Search ads are intent-based — your customer is already looking for what you offer. This lesson covers writing Google ad headlines and descriptions with AI, understanding quality score basics, and thinking about keyword intent.
Choose one of your core services. Ask AI: 'Write Google Responsive Search Ad copy for [service]. Create: 10 headline options (max 30 characters each), 4 description options (max 90 characters each). Include keywords naturally. Focus on: benefit, trust, urgency.'
Pay attention to how AI structures its response. Is it giving you something genuinely useful, or something generic? The difference is almost always in the specificity of your prompt — the more context you give, the better the output.
Applying this in practice
The real skill here isn't getting AI to produce something — it's knowing when the output is good enough to use and when it needs refinement. Review everything AI produces through the lens of your specific audience. If it could have been written for anyone, it needs more work.
AI handles the first 80% — structure, vocabulary, volume. You provide the remaining 20% — your specific audience insight, your brand voice, your judgment about what will land. Neither alone produces great marketing.
5.3 — Social Media Advertising
Facebook, Instagram and LinkedIn ads that convert
Paid social is where many businesses waste money on poorly written ads
Paid social is where many businesses waste money on poorly written ads. This lesson covers writing ad copy for Facebook, Instagram, and LinkedIn — different audiences, different tones, different goals — using AI to generate and test variations fast.
Pick one campaign goal: awareness, leads, or sales. Ask AI: 'Write 3 social ad variations for [goal] for [business]. Platform: [choose one]. Vary the approach: emotional story, rational benefit, social proof. Include primary text, headline, and CTA for each.'
Pay attention to how AI structures its response. Is it giving you something genuinely useful, or something generic? The difference is almost always in the specificity of your prompt — the more context you give, the better the output.
Applying this in practice
The real skill here isn't getting AI to produce something — it's knowing when the output is good enough to use and when it needs refinement. Review everything AI produces through the lens of your specific audience. If it could have been written for anyone, it needs more work.
AI handles the first 80% — structure, vocabulary, volume. You provide the remaining 20% — your specific audience insight, your brand voice, your judgment about what will land. Neither alone produces great marketing.
5.4 — Testing and Iteration
How to use AI to improve ads that aren't working
The best ad writers test obsessively
The best ad writers test obsessively. This lesson shows you how to use AI as a testing partner — diagnosing why an ad underperforms, generating alternative approaches, and iterating systematically rather than guessing.
Take an ad that hasn't performed well (or invent a scenario). Ask AI: 'Here is an ad that is underperforming: [paste ad]. Diagnose what might be wrong with the hook, the body, or the CTA. Then rewrite it three different ways, each fixing a different suspected problem.'
Pay attention to how AI structures its response. Is it giving you something genuinely useful, or something generic? The difference is almost always in the specificity of your prompt — the more context you give, the better the output.
Applying this in practice
The real skill here isn't getting AI to produce something — it's knowing when the output is good enough to use and when it needs refinement. Review everything AI produces through the lens of your specific audience. If it could have been written for anyone, it needs more work.
AI handles the first 80% — structure, vocabulary, volume. You provide the remaining 20% — your specific audience insight, your brand voice, your judgment about what will land. Neither alone produces great marketing.
5.5 — Part 5 Exercise — Your Ad Portfolio
Write a complete set of ads for your next campaign
Write 3 Facebook/Instagram ad variations, 10 Google ad headlines and 4 descriptions, one LinkedIn ad, and a testing plan for your next campaign
Write 3 Facebook/Instagram ad variations, 10 Google ad headlines and 4 descriptions, one LinkedIn ad, and a testing plan for your next campaign.
Four-part exercise: (1) Write 3 social ad variations using different frameworks. (2) Build a complete Google RSA with 10 headlines and 4 descriptions. (3) Write one LinkedIn ad. (4) Create a simple A/B testing plan.
Pay attention to how AI structures its response. Is it giving you something genuinely useful, or something generic? The difference is almost always in the specificity of your prompt — the more context you give, the better the output.
Applying this in practice
The real skill here isn't getting AI to produce something — it's knowing when the output is good enough to use and when it needs refinement. Review everything AI produces through the lens of your specific audience. If it could have been written for anyone, it needs more work.
AI handles the first 80% — structure, vocabulary, volume. You provide the remaining 20% — your specific audience insight, your brand voice, your judgment about what will land. Neither alone produces great marketing.