Creates listing and search-content fields together
The source covers product or listing copy alongside SEO-related fields such as keywords, metadata, or image text when those fields are requested.
Amazon Listing Optimization Prompt is a copyable AI prompt for Amazon sellers. Use it to review an Amazon listing and draft revised title, bullets, search terms and A+ content. Copy the full instruction, add your inputs and check the result before use.
Use Amazon Listing Optimizer to turn verified inputs into a first-pass product-content draft for human review. Amazon Listing Optimizer fits Level 2: The mechanics are simple; good results depend on giving the model clean inputs and a clear review rule. The operator also needs enough store experience to judge the product-content draft against factual corrections, editing time, approval rate, and conversion quality.
This prompt asks the model to review an Amazon listing and draft revised title, bullets, search terms and A+ content; the points below reflect instructions present in the source text.
The source covers product or listing copy alongside SEO-related fields such as keywords, metadata, or image text when those fields are requested.
The complete source is shown below. Copy it from the top right to use it.
You are an Amazon listing optimization expert. When given a product listing, analyze and optimize:
1. TITLE OPTIMIZATION:
- Current title analysis (keyword density, character count)
- Optimized title (200 chars max, front-load primary keyword)
- 3 A/B test variants
2. BULLET POINTS (5 bullets, 500 chars each):
- Bullet 1: Primary benefit + key feature
- Bullet 2: What makes it different (USP)
- Bullet 3: Specs/material/technical details
- Bullet 4: Use cases / who it's for
- Bullet 5: Guarantee / warranty / social proof
3. BACKEND SEARCH TERMS:
- 5-10 high-volume, low-competition keywords
- Competitor brand terms to target
- Misspellings and alternate phrasings
4. A+ CONTENT OUTLINE:
- Module 1: Hero image + brand story
- Module 2: Comparison chart (vs competitors)
- Module 3: Detailed feature breakdown
- Module 4: Lifestyle/use-case imagery brief
5. COMPETITIVE GAP ANALYSIS:
- 3 things top competitors do that this listing doesn't
- Price positioning recommendation
- Review velocity strategy
For each optimization, estimate: expected ranking improvement (1-10), conversion lift (%), and implementation effort (minutes).Copy a starter instruction, add the required inputs, then run one example and review the output.
Do not begin with a store-wide rollout. Pick one reversible task where Amazon Listing Optimizer can help you create, localize, or check product content and visual assets. Use this when the input boundary, owner, and one primary measure from factual corrections, editing time, approval rate, and conversion quality are written down.
Use the Prompt above to help me with this task: Start with one real task.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Do not begin with a store-wide rollout. Pick one reversible task where Amazon Listing Optimizer can help you create, localize, or check product content and visual assets.
Return a practical result and clearly flag anything that needs human review.[TASK_DETAILS][CONSTRAINTS]Collect only the verified product facts, source images, brand rules, target channel, and prohibited claims needed for this test. Remove unrelated personal data and state which actions must never run automatically. Use this when every input has a known source, sensitive fields are minimized, and the approver knows what the trial can read or change.
Use the Prompt above to help me with this task: Prepare the input and guardrails.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Collect only the verified product facts, source images, brand rules, target channel, and prohibited claims needed for this test. Remove unrelated personal data and state which actions must never run automatically.
Return a practical result and clearly flag anything that needs human review.[TASK_DETAILS][CONSTRAINTS]Replace the placeholders in Amazon Listing Optimizer with verified business information. Run one normal example, then one example with a missing field or edge case. Use this when you have a product-content draft that a responsible operator can inspect, and it stayed inside the approved boundary.
Use the Prompt above to help me with this task: Replace the placeholders and run the Prompt.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Replace the placeholders in Amazon Listing Optimizer with verified business information. Run one normal example, then one example with a missing field or edge case.
Return a practical result and clearly flag anything that needs human review.[TASK_DETAILS][CONSTRAINTS]Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time. Use this when factual corrections, editing time, approval rate, and conversion quality has a pre-test baseline, and errors and exceptions are logged separately.
Use the Prompt above to help me with this task: Review it against a baseline.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time.
Return a practical result and clearly flag anything that needs human review.[TASK_DETAILS][CONSTRAINTS]The generated result is a draft; check claims, numbers and operating conditions against source data before publishing, importing or acting on it.
When this instruction drafts marketing or product content, review specifications, comparisons, performance claims, and testimonials against approved evidence before publishing.
Any price, discount, cost, or margin recommendation is only as current as the values you provide. Recheck live prices, tax, shipping, and margin rules before publishing or sending an offer.
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