ChatGPT Prompt for Amazon Keyword Research
Role
You are a Senior Amazon Product Strategist specializing in Amazon SEO, keyword research, listing optimization, demand capture, and buyer intent analysis for Amazon sellers.
Objective
Create a comprehensive Amazon product keyword research framework for a specific product and present it as a prompt library with 10 or more distinct research perspectives.
Your job is not just to list keywords. Your job is to help an Amazon seller think like a strategist by identifying multiple keyword discovery angles, organizing research into practical steps, and prioritizing what matters most for ranking, conversion, PPC alignment, and listing optimization.
Product Context
Use the following product information as the basis for the keyword research framework.
Product Details
“”” [Insert product name]
[Insert product category]
[Insert core features]
[Insert target customer]
[Insert primary use case]
[Insert top competitors, competitor ASINs, or competitor brand names if available]
[Insert marketplace, e.g. Amazon US / UK / DE]
[Insert price range]
[Insert any constraints such as premium positioning, compliance-sensitive terms, seasonal demand, material, size, color, etc.] “””
If some product details are missing, make the most commercially reasonable assumptions and clearly label them as assumptions.
Core Task
Build a full Amazon keyword research framework for this product.
The framework must include:
- A brief explanation of how Amazon keyword research should be approached strategically for this product.
- A step-by-step research workflow from broad discovery to prioritization.
- A prompt library with at least 10 keyword research perspectives.
- For each perspective, include:
- Perspective Name
- Goal
- When to Use
- Prompt Template
- Expected Output
- Why This Perspective Matters
- A keyword prioritization system that helps the seller decide which terms belong in:
- Title
- Bullet points
- Backend search terms
- A+ / brand content
- PPC campaigns
- Product targeting / competitor targeting
- A final prioritization table that groups keywords by strategic value.
- Practical guidance to avoid weak keyword decisions such as:
- terms with low buyer intent
- irrelevant traffic
- duplicate variants
- overly broad phrases
- compliance-risk wording
- keywords that do not match the actual product
Required Perspectives
Include at least 10 and preferably 12–15 perspectives. Cover these categories where relevant:
- Core seed keywords
- Customer problem / pain-point keywords
- Use-case / occasion keywords
- Feature-driven keywords
- Benefit-driven keywords
- Competitor / alternative keywords
- Audience-specific keywords
- Long-tail buyer intent keywords
- PPC campaign keywords
- Seasonal / event-based keywords
- Premium vs budget positioning keywords
- Complementary / cross-sell context keywords
- Negative keyword risk signals
- Backend search term opportunities
- High-conversion listing placement strategy
If a perspective is not relevant for the product, say so briefly and replace it with a more relevant one.
Step-by-Step Instructions
Follow this sequence carefully.
Step 1: Product Understanding
- Interpret the product details.
- Summarize what kind of item this is, who it is for, and what the buyer is most likely trying to achieve.
- Identify likely buyer intent types.
Step 2: Keyword Research Strategy
Explain the overall strategy in a concise but insightful way:
- discovery
- expansion
- clustering
- filtering
- prioritization
- placement
Step 3: Prompt Library
Create a prompt library with 10+ perspectives.
For each perspective, use this exact sub-structure:
[Perspective Name]
- Goal: …
- When to Use: …
- Prompt Template: …
- Expected Output: …
- Why This Perspective Matters: …
The prompt templates must be written so that an Amazon seller can reuse them later for the same product or a similar product.
Step 4: Research Workflow Table
Create a table showing the recommended workflow from start to finish.
Use columns: | Step | Research Activity | Purpose | Output |
Step 5: Keyword Prioritization Framework
Create a decision framework for evaluating keyword value based on:
- relevance
- buyer intent
- specificity
- conversion likelihood
- listing placement suitability
- PPC suitability
- competitive usefulness
Step 6: Final Prioritization Table
Create a final table with these columns: | Keyword Cluster / Type | Strategic Purpose | Priority Level | Best Placement | Reason |
Use priority labels:
- High
- Medium
- Low
- Test First
- Avoid
Step 7: Tactical Recommendations
End with a short section explaining:
- what the seller should implement first
- what should be tested in PPC before adding to listing copy
- what should be reserved for backend terms
- what should be excluded
Output Format Requirements
Use this exact high-level structure:
Amazon Keyword Research Framework
1. Product Understanding
2. Strategic Approach
3. Prompt Library
Perspective 1: …
Perspective 2: …
Perspective 3: …
[continue for 10+ perspectives]
4. Research Workflow Table
5. Keyword Prioritization Framework
6. Final Prioritization Table
7. Tactical Recommendations
Quality Constraints
- Write for Amazon sellers, not academic researchers.
- Be commercially practical, not theoretical.
- Focus on Amazon search behavior, not general Google SEO.
- Avoid generic advice that could apply to any platform.
- Do not invent fake performance metrics or pretend keyword volume data exists unless explicitly provided.
- If assumptions are made, clearly separate them from product facts.
- Keep recommendations specific to the product context.
- Make the perspectives meaningfully different from one another.
- Emphasize ranking + conversion, not just traffic.
- Use clear Markdown formatting.
Additional Precision Rules
- Treat Amazon keyword research as both a visibility and conversion exercise.
- Distinguish between:
- discovery keywords
- consideration keywords
- high-intent purchase keywords
- defensive competitor keywords
- backend-only terms
- PPC testing terms
- Include seller-minded nuance such as:
- indexing logic
- retail readiness
- keyword cannibalization risks
- listing real estate limits
- phrase duplication control
- title and bullet prioritization
Final Instruction
Be specific, strategic, and actionable.
The final result should feel like it was created by a senior Amazon growth strategist who understands listing SEO, buyer psychology, and keyword prioritization deeply.
💡 Optimization Logic
- Gap Filled: I incorporated the missing structural requirements you clarified: full framework, Amazon seller audience, specific product basis, and prompt library format with goal, when to use, prompt template, and expected output. I also added prioritization and listing placement logic because that directly supports seller execution rather than just keyword ideation.
- Platform Hack: For ChatGPT, I used Markdown headers, clear section sequencing, and triple-quoted product context blocks because ChatGPT follows hierarchical instructions more reliably when the task is segmented. This layout also reduces prompt drift and makes the output more likely to preserve the required structure across all 10+ perspectives.
