100 Best Claude Performance Review Prompts for Amazon Sellers

Direct Answer

The best Claude prompts for performance review for Amazon sellers are designed to extract concrete, actionable insights from sales data, reviews, inventory, ads, and operations. They specify roles, tasks, context placeholders, output formats, and constraints to ensure useful, repeatable results across reviews.

Introduction

This page provides a practical, ready-to-use prompt library focused on performance review for Amazon sellers. It helps sellers, managers, and analysts generate structured, action-oriented assessments from data and listings.

Whether you manage a catalog, optimize ads, or streamline fulfillment, these prompts deliver clear insights and ready-to-implement steps for performance reviews on Amazon.

How to Use These Claude Prompts

• Replace placeholders like [storeName], [category], [region], and [SKU] with your own data before running a prompt.
• Add constraints or formats to tailor outputs to your reporting needs, such as a 1-page summary or a 2-column table.
• If you need a different cadence, request a quarterly, monthly, or weekly review format.
• Ask for a comparison to prior periods to establish performance deltas, or request a prioritized action list.
• Whenever outputs include numbers, request a brief explanation of data sources and assumptions to enable trust and reproducibility.
• Verify outputs by cross-checking with your internal dashboards and inventory systems.

100 Best Claude Performance Review Prompts for Amazon Sellers

1. Sales trend analysis prompt: You are an ecommerce analyst. Task: generate a concise performance review section summarizing sales trends for the last quarter for the Amazon store [storeName]. Context: include key SKUs, seasonality, and top growth drivers. Output format: bullet list with sections for overall revenue, unit sales, average price, and contribution margin. Constraints: focus on actionable takeaways, avoid noise, keep to two paragraphs.
2. Inventory health review: Role: Inventory Manager. Task: assess inventory health for Amazon catalog [catalogName] over the past 90 days. Context: highlight sell-through rate, stockouts, overstock risk, and forecast accuracy. Output: structured report with a table of metrics and three concrete recommendations. Constraints: base decisions on historical demand and upcoming promotions.
3. Pricing impact assessment: You are a pricing strategist. Task: evaluate how price changes affected sales on key ASINs during the last promotion window. Context: compare before/after price, competitor parity, and margin impact. Output: concise narrative plus a chart-ready data table showing price, units, revenue, margin. Tone: data-driven.
4. Advertising performance snapshot: Role: Advertising Analyst. Task: generate a performance snapshot for Amazon Ads campaigns during the review period. Context: break down campaigns by Sponsored Products, Sponsored Brands, and Sponsored Display; include ACoS, ROAS, and budget pacing. Output: executive summary plus three recommended optimizations. Constraints: focus on high-impact changes and feasibility.
5. Customer sentiment review: You are a CX specialist. Task: summarize customer sentiment from reviews and Q&A for [productLine]. Context: extract themes, rating distribution, and notable issues. Output: bullet points and a short risk flag with mitigation ideas. Constraints: avoid raw reviewer quotes unless they add value.
6. Fulfillment performance check: Role: Operations Analyst. Task: assess fulfillment metrics for Prime-enabled orders in the last quarter. Context: analyze on-time delivery, stockouts at 3PL, and fulfillment penalties. Output: 1-page report with 4 actionable steps and 2 risk indicators. Constraints: tie to customer satisfaction impact.
7. Top performing listings: You are a marketplace analyst. Task: identify the top 5 listings by revenue growth in the last 60 days for [category]. Context: consider conversion rate, traffic, and detail page quality signals. Output: ranked list with per-listing insights and one improvement per listing.
8. Supply chain bottlenecks: Role: Supply Chain Manager. Task: identify bottlenecks impacting stock availability for [SKU(s)]. Context: map from supplier to fulfillment center, flag lead-time risks and variability. Output: problem tree with 3 root causes and 2 mitigations per cause.
9. Customer return analysis: You are a Returns Specialist. Task: analyze return rate by product and reason codes over the last 180 days for [storeName]. Context: identify patterns, high-cost return drivers, and corrective actions. Output: actionable plan with success metrics.
10. New product launch readiness: Role: Product Launch Analyst. Task: evaluate readiness for upcoming product launch in [category]. Context: assess listing completeness, reviews plan, launch timeline, and PPC setup. Output: launch readiness score and a 2-week action plan.
11. Seasonality planning: You are an Ecommerce Planner. Task: build a seasonality plan for the next 12 weeks for [storeName]. Context: align with promotions, inventory, and ad budgets. Output: calendar with focus themes and KPI targets.
12. Vendor performance check: Role: Vendor Manager. Task: evaluate supplier performance for key vendors over the last two quarters. Context: delivery reliability, quality issues, and price variances. Output: scorecard and 2 joint improvement initiatives.
13. Content quality audit: You are a content auditor. Task: assess product detail pages for top 20 SKUs by revenue in [storeName]. Context: check imagery quality, bullets clarity, A+ content usage, and storefront cohesion. Output: audit report with 10 improvement opportunities.
14. Pricing parity review: Role: Pricing Auditor. Task: compare Amazon pricing parity across marketplaces for [SKU list]. Context: identify undercut risks and margin impact. Output: summary with 5 parity gaps and remediation steps.
15. Customer lifetime value: You are a Data Analyst. Task: compute customer lifetime value for buyers of [brand] on Amazon. Context: use last 24 months of purchases, cohort by first purchase month, and repeat purchase rate. Output: brief insights and 3 optimization ideas.
16. Marketing funnel analysis: Role: Growth Analyst. Task: map the marketing funnel from discovery to purchase for [category]. Context: identify drop-off points and high-converting touchpoints. Output: funnel diagram description and 2 recommendations.
17. ACOS optimization plan: You are a PPC specialist. Task: propose an optimization plan to reduce overall ACOS for [storeName] without sacrificing revenue. Context: adjust bids by SKU, test negative keywords, and refine audience targeting. Output: 6-week action plan with success metrics.
18. Product page experiment ideas: Role: Experiment Designer. Task: propose 5 controlled A/B tests to improve conversion on product pages for [category]. Context: specify test variant, sample size, duration, and acceptance criteria. Output: test plan summary.
19. Vendor risk assessment: You are a risk analyst. Task: assess third-party vendor risks for the Amazon business in [region]. Context: include financial stability, compliance, and supply continuity. Output: risk register with mitigation owners.
20. Logistics cost review: Role: Logistics Analyst. Task: evaluate freight and inbound costs for the last three months. Context: identify cost-saving opportunities and carrier performance. Output: cost-reduction plan with quarterly savings target.
21. Advertising mix balance: You are an Ad Ops Specialist. Task: assess the balance across Sponsored Products, Brands, and Display campaigns for [storeName]. Context: ensure optimal allocation for demand generation and efficiency. Output: recommended budget mix and 3 tests.
22. Product ranking drivers: Role: Data Scientist. Task: determine factors driving top product rankings on Amazon for [category]. Context: include reviews, images, price, and availability signals. Output: rank factors with scoring and 2 tactical levers.
23. Negative feedback loop: You are a CX engineer. Task: design a process to capture and close critical negative feedback for [productLine]. Context: automation triggers, ownership, and response templates. Output: workflow diagram description.
24. Cross-sell and up-sell plan: Role: Merchandising Strategist. Task: design cross-sell and up-sell suggestions for bundles in [storeName]. Context: customer journey touchpoints, price points, and inventory fit. Output: 3 bundle concepts with expected lift.
25. Fulfillment SLA tracking: You are an Operations Analyst. Task: track supplier SLA adherence for Amazon orders in [region]. Context: flags delays, penalties, and corrective actions. Output: SLA dashboard summary.
26. Returns avoidance plan: Role: Returns Prevention Specialist. Task: develop a plan to reduce preventable returns for [SKU list]. Context: root causes, messaging, and packaging improvements. Output: 4 actionable steps and metrics.
27. Customer review ranking: You are a Review Analytics Lead. Task: rank top customer review themes by impact on conversion for [product]. Context: map themes to sentiment and feature requests. Output: prioritized theme list and 2 product implications.
28. Listing localization plan: Role: Localization Manager. Task: plan listing localization for new markets in [regions]. Context: translate, imagery adaptation, and compliance notes. Output: rollout plan with milestones.
29. Seasonal demand forecast: You are a Demand Planner. Task: forecast seasonal demand for [category] next quarter. Context: consider historical data, promotions, and macro factors. Output: forecast table with 3 scenarios.
30. Inventory replenishment model: Role: Inventory Planner. Task: build a replenishment model for high-turn SKUs in [storeName]. Context: lead time, service level, and safety stock. Output: model summary and reorder recommendations.
31. Sales channel comparison: You are a Channel Analyst. Task: compare Amazon performance to other channels for [brand]. Context: revenue, margin, and growth rate. Output: comparative brief with 3 takeaways.
32. Customer segmentation review: Role: Market Analyst. Task: segment Amazon customers for [storeName] by value and behavior. Context: include repeat purchasers and at-risk segments. Output: segmentation map with 4 segments and actions.
33. Promotion effectiveness audit: You are a Promotions Auditor. Task: assess the ROI of current promotions in [category]. Context: consider discount depth, traffic, and margin. Output: audit with 5 improvement ideas.
34. Listing image quality check: Role: Creative Auditor. Task: evaluate product images for top 10 SKUs by revenue in [storeName]. Context: image quality, consistency, and accessibility. Output: image quality scorecard and 3 image improvements.
35. Review response framework: You are a Customer Communications Lead. Task: design a standardized review response framework for [brand] on Amazon. Context: tone, escalation path, and response time targets. Output: framework document with templates.
36. PPC keyword harvest: Role: PPC Analyst. Task: generate a 2-week keyword harvest plan for [storeName]. Context: identify high-potential terms, negative keywords, and bid adjustments. Output: list of 25 keywords with rationale.
37. Product launch risk map: You are a Launch Risk Analyst. Task: map risks for a new product launch in [category]. Context: supply, demand, and listing readiness. Output: risk map with mitigations and owners.
38. Review KPI heatmap: Role: Data Visualizer. Task: create a KPI heatmap for Amazon performance in [storeName]. Context: include revenue, orders, ACoS, and rating score. Output: heatmap description and interpretation notes.
39. A/B test prioritization: You are a Experiment Prioritizer. Task: rank 5 potential A/B tests for boosting conversion on [productLine]. Context: impact, effort, and risk. Output: prioritized test schedule with success criteria.
40. SKU rationalization: Role: Merchandising Lead. Task: propose SKU pruning for [storeName] based on 12-month performance. Context: profitability, cannibalization, and SKU count targets. Output: pruning list with rationale.
41. Ad creative testing plan: You are an Ad Creative Strategist. Task: design 4 ad creative variants for [SKU] and 2 audience targets. Context: messaging and visual cues. Output: test plan with success metrics.
42. Review metric normalization: Role: Data Engineer. Task: normalize disparate performance metrics across regions for Amazon business in [region]. Context: ensure comparability. Output: normalization rules and sample calculations.
43. Negative review mitigation: You are a CX Specialist. Task: craft a proactive response plan for common negative review themes in [category]. Context: escalation, compensation policy, and follow-up. Output: 6 templates.
44. Fulfillment center routing: Role: Logistics Planner. Task: optimize routing of inventory to fulfillment centers for [region]. Context: cost, speed, and service levels. Output: routing plan with 3 scenarios.
45. Competitive price tracking: You are a Market Intelligence Analyst. Task: set up a competitive price tracking for top competitors in [category]. Context: cadence, data points, and alert thresholds. Output: monitoring plan and 2 alert rules.
46. Brand health check: Role: Brand Manager. Task: assess Amazon brand health for [brand] over the last quarter. Context: share of voice, rating momentum, and content quality. Output: brief with 4 actions.
47. Conversion rate optimization: You are a CRO Specialist. Task: outline 5 experiments to improve conversion on product pages for [storeName]. Context: hypotheses, metrics, and duration. Output: experimentation plan.
48. Logistics lead-time analysis: Role: Supply Chain Analyst. Task: analyze inbound lead times for top suppliers of [SKU]. Context: variability and reliability. Output: lead-time dashboard and 2 reductions.
49. Account health summary: You are an Account Manager. Task: summarize Amazon seller account health for [storeName]. Context: policy compliance, performance metrics, and warning signals. Output: executive brief with remediation plan.
50. Customer experience map: Role: CX Architect. Task: create a customer experience map for the Amazon buying journey of [category]. Context: touchpoints and friction points. Output: map with 6 stages and 2 improvements per stage.
51. Refund policy clarity: You are a Policy Writer. Task: draft a clear refund and return policy update for [storeName] on Amazon. Context: eligibility, timelines, and exceptions. Output: policy draft.
52. Product compliance review: Role: Compliance Auditor. Task: verify product listings meet regulatory requirements for [region]. Context: labeling, claims, and safety standards. Output: compliance checklist with remediation items.
53. Brand collaboration opportunities: You are a Partnerships Manager. Task: identify 3 potential brand collaborations for [storeName] on Amazon. Context: audience fit, co-marketing plans, and expected impact. Output: collaboration brief.
54. Crisis response playbook: Role: PR Lead. Task: draft a crisis response playbook for issues affecting Amazon listings in [category]. Context: communication templates and escalation paths. Output: playbook outline.
55. Packaging optimization: You are a Packaging Engineer. Task: propose 4 packaging changes to reduce damages and improve unboxing experience for [SKU]. Context: cost and supply impact. Output: recommended changes with ROI.
56. Listing clashing analysis: Role: Listing Strategist. Task: identify potential keyword cannibalization across top 50 SKUs in [storeName]. Context: rank by revenue and conversion. Output: mitigation plan.
57. Product aging risk: You are a Lifecycle Manager. Task: assess risk of product aging for [category] and plan refreshes. Context: price, feature updates, and review cadence. Output: refresh plan with milestones.
58. Fulfillment cost per order: Role: Cost Analyst. Task: compute fulfillment cost per order for [storeName] by region. Context: split by prep, pick, pack, and shipping. Output: cost report and optimization ideas.
59. AEO readiness check: You are an Internal Auditor. Task: ensure readiness for Amazon events and promos in [region]. Context: timing, assets, and approvals. Output: readiness score and 2 blockers.
60. Returns by reason: Role: Returns Analyst. Task: break down returns by reason code for [SKU] over the last year. Context: cost impact and prevention opportunities. Output: reason heatmap and action plan.
61. Product lifecycle stage: You are a Product Lifecycle Analyst. Task: classify each top SKU into intro, growth, maturity, or decline for [storeName]. Context: revenue trend and review sentiment. Output: lifecycle matrix with actions.
62. Fraud risk review: Role: Security Analyst. Task: evaluate fraud risk signals in Amazon orders for [storeName]. Context: unusual patterns, account access, and payment anomalies. Output: risk brief with mitigations.
63. Vendor scorecard update: You are a Vendor Relations Lead. Task: refresh vendor scorecards for the last quarter. Context: on-time delivery, quality, cost changes, and contract adherence. Output: updated scorecards with 2 improvement items per vendor.
64. Top customers insights: Role: Loyalty Manager. Task: identify top 5 high-value customers by lifetime spend in [storeName]. Context: repeat purchase rate and engagement. Output: profiles and tailored offer ideas.
65. Review response speed: You are a CX Ops Manager. Task: set target response times for Amazon reviews for [brand]. Context: escalation thresholds and templates. Output: target metrics and quick-start templates.
66. Promotions calendar: Role: Promos Planner. Task: create a 6-week promotions calendar for [storeName]. Context: inventory, margin, and anticipated demand. Output: calendar with promo types and KPI targets.
67. Detail page value map: You are a Content Strategist. Task: map each detail page element to customer value for [SKU]. Context: critical features and objections. Output: value map with improvement ideas.
68. Channel risk mitigation: Role: Channel Risk Manager. Task: identify risks specific to Amazon presence in [region]. Context: policy changes, supply, and competition. Output: risk register with mitigations.
69. Listing feature parity: You are a Product Manager. Task: ensure Amazon listing features meet competitor capabilities in [category]. Context: bullets, A+ content, video. Output: feature gap report.
70. Pricing elasticity test: Role: Pricing Scientist. Task: test price elasticity for top 6 SKUs in [storeName]. Context: demand response to price changes. Output: elasticity curves and recommended price ranges.
71. Product margins review: You are a Financial Analyst. Task: compute gross margin by SKU for the last quarter in [storeName]. Context: costs, fees, and returns. Output: margin table with 6 top contributors.
72. Advertising experiment slate: Role: Ad Scientist. Task: propose 4 experiments to test new ad creatives and audiences for [SKU]. Context: predicted lift and risk. Output: experiment slate with timeline.
73. Customer risk indicators: You are a Risk Analyst. Task: identify 3 leading indicators predicting churn for Amazon buyers in [category]. Context: purchase frequency and satisfaction signals. Output: risk indicators with monitoring plan.
74. Order defect analysis: Role: Quality Control Lead. Task: analyze order defects for [storeName] and root causes. Context: packing errors, shipping delays, and mislabeling. Output: defect taxonomy and 3 fixes.
75. Brand safety audit: You are a Brand Safety Auditor. Task: assess listing content for policy compliance and brand safety in [region]. Context: image, language, claims. Output: safety scorecard with 2 remediation steps.
76. Fulfillment center efficiency: Role: Ops Excellence Lead. Task: benchmark fulfillment center metrics for [region] and identify efficiency gains. Context: pick rate, pack time, and dock-to-stock. Output: efficiency report with 3 recommendations.
77. AEO events readiness: You are an Events Readiness Analyst. Task: prepare for major Amazon shopping events in [region]. Context: inventory, ads, and landing pages. Output: readiness plan with checklists.
78. Content localization risk: Role: Localized Content Lead. Task: identify localization risks for listings in [regions]. Context: cultural nuances and regulatory constraints. Output: risk list with mitigation actions.
79. Sustainability messaging plan: You are a Brand Communications Lead. Task: craft sustainable packaging and messaging for Amazon listings in [category]. Context: certifications and customer expectations. Output: plan with 3 examples.
80. International listing clean-up: Role: International SEO Lead. Task: audit Amazon listings for [regions] and fix common issues. Context: language, currency, and tax notes. Output: clean-up playbook.
81. Product rating uplift plan: You are a Rating Strategy Lead. Task: design 4 actions to improve average rating for [SKU] without heavy discounting. Context: feedback gating and follow-up. Output: plan with expected impact.
82. Inventory aging alerting: Role: Inventory Analytics. Task: set aging thresholds and alerts for slow-moving stock in [region]. Context: obsolescence risk and write-offs. Output: alert criteria and response workflow.
83. Fraud detection prompts: You are a Security Prompt Engineer. Task: create a set of Claude prompts to detect fraudulent orders on Amazon for [storeName]. Context: anomaly signals and escalation. Output: prompt bundle with 6 prompts.
84. Product listing governance: Role: Governance Lead. Task: implement listing governance for Amazon in [region]. Context: approval workflows and version control. Output: governance plan.
85. Top performing reviews: You are a Review Strategist. Task: identify 3 reviews that reveal critical product strengths for [SKU] and suggest how to feature them. Context: sentiment and business impact. Output: highlighting notes and usage suggestions.
86. Shipping speed optimization: Role: Logistics Lead. Task: optimize shipping speeds for high-velocity products in [region]. Context: carrier selection and packing methods. Output: plan with two pilot adjustments.
87. Product performance benchmark: You are a Benchmark Analyst. Task: compare Amazon performance of [storeName] against 3 top competitors in [category]. Context: revenue growth, margins, and reviews. Output: benchmark summary with 5 takeaways.
88. Customer feedback loop: Role: Feedback Program Manager. Task: implement a closed-loop customer feedback process for [storeName]. Context: data capture, routing, and action closure. Output: process map with 4 stages.
89. Discount strategy review: You are a Discount Strategist. Task: review current discounting approach for [storeName] and propose alternatives. Context: cannibalization risk and margins. Output: 4 options with trade-offs.
90. Product information accuracy: Role: Info Quality Lead. Task: verify core product attributes for [SKU] across listing sections. Context: titles, bullets, and specs. Output: accuracy score and fixes.
91. Listing cross-sell ideas: You are a Merchandising Analyst. Task: propose 4 cross-sell ideas within a product family in [storeName]. Context: bundles and pricing. Output: idea sheet with expected lift.
92. Post-purchase engagement: Role: Lifecycle Marketer. Task: design post-purchase engagement sequences for [category]. Context: emails, messages, and timing. Output: sequence blueprint with 3 touchpoints.
93. Content quality rubric: You are a Content Architect. Task: create a rubric to evaluate listing content quality for [region]. Context: clarity, completeness, and accessibility. Output: rubric with 10 criteria.
94. Return reason remediation: Role: Returns Lead. Task: map top return reasons to remediation actions for [SKU]. Context: packaging, instructions, and product quality. Output: remediation plan.
95. Lifecycle triggers: You are a Growth Engineer. Task: define lifecycle triggers that optimize retention for Amazon buyers in [category]. Context: onboarding, usage, and re-engagement. Output: trigger matrix with actions.
96. Operational risk matrix: Role: Risk Manager. Task: build an operational risk matrix for the Amazon business in [region]. Context: probability, impact, and controls. Output: matrix with 6 risks and owners.
97. Compliance training brief: You are a Training Specialist. Task: draft a concise compliance training brief for Amazon policies relevant to [storeName]. Context: updates and practical examples. Output: training note.
98. Data hygiene checklist: Role: Data Steward. Task: create a checklist to maintain data hygiene for Amazon performance metrics in [region]. Context: data sources and validation. Output: checklist with 12 items.
99. Executive briefing template: You are an Executive Assistant. Task: draft a 1-page briefing for the CTO on Amazon performance in [storeName]. Context: highlights, risks, and action items. Output: briefing text.
100. Next quarter priorities: Role: Strategic Planner. Task: identify top 5 priorities for the Amazon business in [storeName] for the next quarter. Context: impact, effort, and dependencies. Output: prioritized list with success criteria.

Best Practices

• Use role-based prompts to ensure outputs align with stakeholder needs (e.g., CX, Ops, Finance).
• Combine metrics from multiple prompts to assemble a cohesive review with executive summaries and detailed follow-ups.
• Lock in output formats (tables, bullet points, or checklists) to streamline reporting and meeting workflows.
• Reuse prompts with standardized data templates to improve consistency across reviews.
• Keep prompts updated with current Amazon policies, fee changes, and feature updates to maintain relevance.

Common Mistakes to Avoid

• Using vague prompts that produce generic insights without clear actions.
• Forgetting to replace placeholders with real data, leading to irrelevant results.
• Overloading prompts with too many goals, causing outputs to be unfocused.
• Ignoring data provenance or assumptions, which breaks trust in the results.
• Not validating outputs against your internal data or dashboards.

FAQ

What is a performance review prompt for Amazon sellers best used for?

It is best used to generate structured, actionable insights on sales, inventory, ads, and customer feedback to guide quarterly or periodic performance reviews.

How should I customize prompts for my store?

Replace placeholders such as [storeName], [category], [region], and [SKU] with your actual data and specify date ranges relevant to your review period.

Can I assemble outputs into a single report?

Yes. Use prompts that require an executive summary plus detailed sections, then consolidate the results into a 1- to 2-page report.

What outputs should I expect from these prompts?

You should get concise summaries, KPI tables, actionable recommendations, and clearly defined owners and timeframes for follow-up.

How do I ensure outputs are reliable?

Cross-validate Claude outputs with your internal analytics dashboards, historical data, and supplier reports; ask for data sources and assumptions where needed.

Are these prompts suitable for new sellers?

Yes, many prompts include fixed structures and placeholders that can be filled with basic data to produce initial, usable performance reviews.