Create a practical prompt pack for my Amazon selling business. My business context is [BUSINESS CONTEXT]. My product and catalog details are [PRODUCT DETAILS]. My current priorities are [CURRENT PRIORITIES]. My data and source materials available are [AVAILABLE DATA]. My marketplace and compliance constraints are [MARKETPLACE AND CONSTRAINTS]. Produce 10 copy-paste prompts for these workstreams: keyword and listing brief, title and bullet rewrite, A+ content outline, customer-review theme analysis, PPC search-term analysis, competitor comparison, inventory reorder planning, customer-service response draft, promotion plan, and weekly operating review. For every prompt: 1. Write it as an instruction I can paste into ChatGPT, Claude, or Gemini, with its own square-bracket inputs.
2. State the exact deliverable, such as a table, ranked list, draft, calculation worksheet, or decision memo. 3. Include task-specific guardrails. Listing copy must avoid unsupported product claims, prohibited medical or comparative claims, keyword stuffing, and competitor trademarks. Inventory work must separate known figures from assumptions and show the reorder formula. Customer-service work must not promise refunds, replacements, or policy outcomes I have not approved. 4. Require the model to label unknowns, preserve customer privacy, and distinguish marketplace policy guidance from verified policy text. Start with a one-paragraph note on which business information I should keep current before using the pack. Then present the 10 prompts in a numbered list, followed by a one-line example use case for each. Prioritize my stated current priorities first. Before answering, check that no prompt tells the model to fabricate sales data, reviews, certifications, test results, or Amazon policy. Ask up to 3 clarifying questions only if a required input is missing.
Fill in
| Placeholder | What to enter | Example |
|---|---|---|
| [BUSINESS CONTEXT] | Describe your selling model, marketplace, team size, margins, and operating stage. | US FBA seller with a two-person team selling private-label kitchen organizers; average gross margin is 31% before ads. |
| [PRODUCT DETAILS] | List the products, variants, materials, prices, differentiators, and known limitations. | Bamboo drawer divider, adjustable 17–22 inches, set of four, $29.99, includes foam ends; not dishwasher safe. |
| [CURRENT PRIORITIES] | State the two or three problems or goals you need to address now. | Reduce wasted PPC spend, improve the main listing conversion rate, and avoid a stockout before November. |
| [AVAILABLE DATA] | List the reports, listing copy, search-term data, reviews, costs, and inventory figures you can provide. | Last 90 days of search-term report, current listing, 250 review exports, unit cost, lead time, current on-hand units, and weekly sales. |
| [MARKETPLACE AND CONSTRAINTS] | State the Amazon marketplace, category rules, brand restrictions, and claims you must avoid. | Amazon.com Home & Kitchen; no sustainability certification, no health claims, and no competitor brand names in copy. |
How to use
- Replace the business context with the facts you can verify from Seller Central, supplier documents, and your product files.
- Run only the prompt for the task in front of you, then paste the relevant report or source material rather than relying on memory.
- For listing or policy-sensitive work, compare every claim against product documentation and the current Seller Central policy page.
- Follow up with: “Turn the recommendation into a task list with owner, source data needed, decision rule, and deadline.”
Variations
Listing audit
Use when an existing listing is underperforming or needs a compliance-focused rewrite.
Audit this Amazon listing for clarity, conversion, search relevance, and claim risk. Listing: [CURRENT LISTING]. Product facts and documentation: [PRODUCT FACTS]. Target customer and use case: [TARGET CUSTOMER]. Category and marketplace: [CATEGORY]. First return a table of unsupported claims, missing purchase-decision details, repetitive keywords, and confusing wording. Then draft a title, five bullets, and a backend-keyword plan. Do not use competitor trademarks, invent certifications or test results, or make claims unsupported by [PRODUCT FACTS]. Label statements that require category-policy verification.
Reorder plan
Use when you have sales history and need a defensible purchase-order decision.
Build an inventory reorder recommendation from this data: [WEEKLY SALES]. Current sellable units: [ON-HAND INVENTORY]. Inbound units and arrival dates: [INBOUND INVENTORY]. Supplier lead time: [LEAD TIME]. Desired safety-stock rule: [SAFETY STOCK]. Account for seasonality or promotions only if I provide evidence. Show the formula, assumptions, stockout date range, recommended order quantity, and sensitivity if weekly demand is 20% higher or lower. Separate calculated results from judgment calls. Do not invent demand data. Flag information that would materially change the purchase order.
Review insights
Use when you want product and listing improvements from customer feedback.
Analyze these Amazon reviews: [REVIEW TEXT OR EXPORT]. Product facts: [PRODUCT FACTS]. Review period and count: [PERIOD AND COUNT]. Group feedback into recurring themes, distinguishing product defects, expectation gaps, packaging or shipping problems, use-instruction gaps, and feature requests. For each theme, report representative paraphrases, apparent frequency, severity, likely root cause, and a recommended action. Do not treat a few reviews as a market-wide statistic or invent numerical sentiment scores. End with the three actions most likely to reduce avoidable negative reviews.
Tips
- Use exports with dates and counts for review or PPC analysis; a pasted handful of examples can reveal themes but cannot support a frequency claim.
- Treat Amazon policy output as a checklist of items to verify in Seller Central, especially for supplements, cosmetics, children’s products, and environmental claims.
- For inventory decisions, give the model sellable inventory, inbound dates, supplier lead time, and a safety-stock rule; sales velocity alone is not enough.
- Keep an approved product-facts sheet so title, bullets, ads, support replies, and A+ content do not drift into inconsistent claims.
FAQ
Can ChatGPT write Amazon listings?
Yes, if you provide verified product facts and category constraints. Review claims, character limits, restricted terms, and current policy before publishing.
Can AI access my Seller Central data?
Not unless you connect a tool or paste/export the data yourself. Prompt outputs are only as reliable as the figures and documents supplied.
Should AI choose my PPC bids?
It can help analyze search terms and calculate decision rules, but bid changes should reflect your actual conversion, margin, inventory position, and campaign structure.