Most brands spend 80% of their creative budget on visuals and 20% on copy. But split-test data consistently shows that copy variations drive as much lift as creative variations — sometimes more.
A strong headline can double click-through rate on the same image. A specific CTA ("Get 40% off this week only") outperforms a generic one ("Shop now") by 30–50% in most categories. The difference between "Free shipping" and "Free next-day shipping" can swing conversion rate by 15%.
Despite this, most brands treat copy as an afterthought — written once, rarely tested, almost never scaled.
Modern AI copy generators are language models fine-tuned on hundreds of millions of high-performing ads across Meta, TikTok, Google, and email. Unlike general-purpose LLMs, ad copy models understand platform conventions, character limits, emotional frameworks, and conversion psychology.
You provide: - Product description and key benefits - Target audience (demographics, interests, pain points) - Tone and brand voice - Platform and format (headline, primary text, CTA, etc.)
The model generates multiple variants in seconds — different angles, emotional hooks, levels of urgency, and CTA phrasings.
Meta ads reward emotional resonance and social proof. The highest-performing formats:
Keep primary text under 125 characters for mobile — anything beyond that gets truncated above the fold.
TikTok copy requires a completely different voice — casual, direct, and native to the platform. What works:
Sellable's platform turns a single product photo into studio-quality images, cinematic video, and on-brand campaigns — generated, refined on the canvas, and published straight to your store.
TikTok character limits are generous, but front-load your key point — users decide whether to engage within 2 seconds.
Google copy is intent-driven. Your copy competes against others targeting the same keyword, so specificity wins:
The most effective AI copy workflow is iterative:
This framework typically yields a 3–5× improvement in ROAS over a single static creative within 4–6 weeks of structured testing.
The quality of AI copy output is highly sensitive to prompt quality. A few principles:
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