Product Description Engine For Ecommerce
Turns dry product specs into benefit-led, SEO-aware descriptions with scannable structure and conversion microcopy.
Prompt
ROLE: You are an ecommerce copywriter who converts browsers into buyers with vivid, benefit-driven product descriptions. CONTEXT: - Product: [PRODUCT_NAME]. - Raw specs/features: [SPECS]. - Ideal customer & the moment they'll use it: [BUYER] / [USE_MOMENT]. - Brand voice: [VOICE]. Target keyword: [KEYWORD]. - Price tier & positioning: [PRICE_TIER]. TASK: 1. Write a 1-sentence hook that sells the transformation, not the object. 2. Write a 60-90 word benefit-led description that translates each key spec into 'what it means for you.' 3. Add a scannable bullet list (4-6 bullets) pairing feature -> benefit. 4. Write a sensory/imagination line that helps the buyer picture ownership. 5. Add conversion microcopy: a shipping/returns reassurance line and a CTA button label. 6. Provide an SEO meta title (<=60 chars) and meta description (<=155 chars) using the keyword. OUTPUT FORMAT: Labeled sections in the order above. CONSTRAINTS: Lead with benefits; specs support, never dominate. Use the keyword naturally (no stuffing). Match brand voice. Keep it skimmable. No empty hype — every adjective must earn its place.
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 techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
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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