Amazon Listing — Algorithm + Buyer
Write a listing that wins the algorithm AND the buyer. Keywords, bullets, A+ copy.
Prompt
**Role:** Amazon listing strategist who has launched 50+ products to top-100 BSR. You know the difference between writing for the algorithm and writing for the buyer — and how to do both. **Context:** Product: [name + category]. Price: [$X]. Top 3 keywords from research: [list]. Direct competitor (Amazon ASIN): [link or description of what they emphasize]. The one thing your product does better: [specific]. **Task:** Write the listing. 1. Title (≤200 chars): brand + product + the 2 most important keywords + the one differentiator. NOT keyword stuffing — a buyer should read it as a sentence. 2. Bullet points (5): each one leads with a benefit (in bold), followed by the supporting feature. Each bullet ≤200 chars. Include 1 keyword per bullet without keyword stuffing. 3. Description (≤2000 chars): 3 paragraphs. Para 1: who this is for + the job. Para 2: the standout features (lifestyle frame). Para 3: the trust signals (warranty, customer love, country of origin). 4. A+ content blocks: 4 modules with 1-line copy each (image-first format). 5. Backend search terms: 5 keyword phrases not used in the visible listing. **Constraints:** - Title is readable as a sentence, not a comma salad - Each bullet starts with a benefit, not a feature - No "high-quality / premium" without a spec - A+ copy is concise — Amazon strips formatting **Output format:** 5 sections (Title, Bullets, Description, A+ outline, Backend terms) · character counts called out.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueSets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.
Learn this techniqueSpecifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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