100 Best Claude KPI and Dashboard Prompts for Amazon Sellers

Direct Answer

The best Claude prompts for KPI and dashboard for Amazon sellers are a curated toolkit of precise, role based tasks that guide Claude to return actionable metrics, dashboards, and recommended actions. Use them to build reliable, monitorable KPIs and ready to publish dashboards for Amazon performance.

Introduction

This page is a practical prompt library focused on KPI and dashboard prompts for Amazon sellers. It provides concrete prompts you can copy and run in Claude to extract analytics, monitor performance, and drive decisions.

Designed for Amazon sellers, analysts, and marketing teams, these prompts help you track sales, margins, inventory, ads, and more with consistent outputs.

How to Use These Claude Prompts

• Replace placeholders like [industry], [audience], and [constraints] with your data and context.
• Add constraints such as date ranges, top N units, or specific KPI targets to steer results.
• Request outputs in formats like JSON or CSV and specify fields you need.
• Verify outputs by cross-checking totals and filtering for obvious anomalies.
• Save prompts as reusable templates and adapt per region or product group if needed.

100 Best Claude KPI and Dashboard Prompts for Amazon Sellers

1. Sales by ASIN trend: Role: Data analyst. Task: Generate a time-series summary of daily sales by ASIN for the last 90 days from provided CSV data. Context: You have columns date, asin, units_sold, revenue. Output format: JSON with date, asin, units_sold, revenue, and a 7-day moving average. Constraints: Include only top 10 ASINs by revenue, handle missing data gracefully.
2. ACoS by campaign breakdown: Role: Advertising specialist. Task: Produce a dashboard-ready breakdown of Advertising Cost of Sale (ACoS) by campaign and ad group for the last 60 days using the input dataset with fields campaign_id, ad_group, spend, sales, orders. Output: CSV lines with campaign_id, ad_group, total_spend, total_sales, total_orders, ACoS = spend/sales, and a KPI flag if ACoS is above target.
3. Inventory health check: Role: Operations analyst. Task: Assess inventory health by SKU using fields sku, on_hand, forecast_demand, lead_time, days_of_supply. Output: a ranked list of SKUs with days_of_supply low risk threshold, recommended reorder quantities, and a CSV-ready table.
4. Gross margin by product: Role: Finance analyst. Task: Compute gross margin by product using revenue, cost_of_goods_sold, and sku. Context: Include a filter to show only active SKUs and group by category. Output: JSON with sku, category, revenue, cogs, gross_margin, gross_margin_pct.
5. Month-over-month growth heatmap: Role: Data visualization specialist. Task: Create a heatmap data structure of MoM revenue per month by category for the last 12 months. Output: JSON suitable for a heatmap widget with category, month, revenue, growth_rate.
6. Top products by profitability: Role: Business analyst. Task: List top 20 SKUs by profitability margin, defined as (revenue - COGS) / revenue, for the last quarter. Output: CSV with sku, revenue, cogs, gross_profit, margin.
7. Ad spend efficiency by keyword: Role: PPC analyst. Task: Summarize ad spend efficiency by keyword for the last 30 days: total_spend, total_sales, attributed_orders, ACoS, ROAS. Output: JSON array with keyword, spend, sales, orders, acos, roas.
8. Forecast accuracy tracker: Role: Forecast analyst. Task: Compare forecasted vs actual sales for the last 8 weeks by product. Output: CSV with product, forecast, actual, variance, variance_pct, and a flag indicating whether forecast was within ±10%.
9. Return rate insights: Role: Quality and operations. Task: Provide a summary of returns by reason code for the last quarter, with rate per product and suggested actions. Output: JSON with sku, reason, returns, total_units, return_rate, recommended_action.
10. Pricing impact simulation: Role: Pricing strategist. Task: Model potential revenue impact for a 5% price change on top 50 SKUs, assuming elasticity and demand shift. Output: JSON with sku, current_price, projected_price, projected_units, projected_revenue, note on elasticity assumption.
11. Cash flow snapshot: Role: Finance analyst. Task: Build a monthly cash flow snapshot from sales, refunds, fees, and net profit. Output: CSV with month, inflows, outflows, net_cash, cumulative_cash.
12. Customer lifetime value: Role: CRM analyst. Task: Estimate 12 month customer lifetime value by cohort using repeat_purchase_rate and average_order_value. Output: JSON with cohort, ltv, confidence_interval, assumptions.
13. Vendor performance score: Role: Operations manager. Task: Score vendors on on-time delivery, defect rate, and fill rate using last 12 months data. Output: CSV with vendor_id, on_time, defect_rate, fill_rate, score.
14. Shipping cost per unit: Role: Logistics analyst. Task: Calculate average shipping cost per unit by carrier and region for the last quarter. Output: JSON with carrier, region, avg_cost_per_unit, total_units.
15. Refund trend analysis: Role: Customer operations. Task: Identify refund trend by product and reason over 6 months. Output: CSV with sku, month, refunds, refund_rate, top_reason.
16. Inventory turnover rate: Role: Inventory analyst. Task: Compute inventory turnover rate by SKU over the last year and flag slow movers. Output: JSON with sku, turnover_rate, category, is_slow_mover.
17. Click-through rate by listing: Role: Content analyst. Task: Provide CTR by product listing from ads and organic traffic over 60 days. Output: CSV with listing_id, source, impressions, clicks, ctr.
18. A/B test results summary: Role: Experiment lead. Task: Summarize A/B test outcomes for title or image variants, including statistical significance, uplift, and recommended winner. Output: JSON with test_id, variant, metric, p_value, significance, recommendation.
19. Best seller cluster map: Role: BI analyst. Task: Cluster products into performance-based groups using revenue, units_sold, and margin. Output: JSON with cluster_id, members, summary_stats.
20. Ad budget pacing: Role: PPC strategist. Task: Recommend daily and weekly ad budget pacing to meet quarterly revenue target, adjusting for seasonality. Output: CSV with period, planned_budget, actual_spend, gap, notes.
21. Sequence optimization prompts: Role: Marketing ops. Task: Propose a sequence of 5 optimization prompts to iteratively improve product pages and ads. Output: JSON with step, action, data_needed, success_criteria.
22. SKU profitability heatmap: Role: Finance analyst. Task: Produce a 2D heatmap of profitability by category and SKU. Output: JSON with category, sku, margin, color_label.
23. Fulfillment channel mix: Role: Logistics analyst. Task: Show fulfillment channel mix (FBM vs FBA) by month and impact on shipping times. Output: CSV with month, channel, orders, avg_fulfillment_days.
24. Discount impact analysis: Role: Revenue manager. Task: Quantify revenue impact of discounts by product tier during promo period. Output: JSON with tier, discount_pct, revenue_increase, margin_change.
25. New product viability: Role: Product analytics. Task: Assess viability of a new product using market size, expected margin, and cannibalization risk. Output: JSON with product_id, viability_score, key_risks, recommendation.
26. Forecast vs actual by region: Role: Forecast analyst. Task: Compare regional sales forecast to actual by region for last 6 months. Output: CSV with region, forecast, actual, variance, variance_pct.
27. Campaign health score: Role: PPC manager. Task: Create a health score for each campaign using ACoS, ROAS, spend pace, and reach. Output: JSON with campaign_id, score, drivers.
28. Inventory aging report: Role: Inventory control. Task: List oldest inventory by days in stock and forecast turnover impact. Output: CSV with sku, days_in_stock, forecast_turnover, action_recommendation.
29. Orders per day trend: Role: Ops analyst. Task: Generate daily orders trend for last 60 days by product category. Output: JSON with date, category, orders.
30. Unit economics digest: Role: Finance analyst. Task: Provide unit economics summary for top 100 SKUs, including price, cogs, shipping, fees, and contribution margin. Output: CSV.
31. Return by product cohort: Role: Product analyst. Task: Analyze returns by product cohort over last 12 months and recommend mitigations. Output: JSON with sku, cohort_month, return_rate, mitigation.
32. Supplier lead time forecast: Role: Procurement. Task: Forecast supplier lead time variability and impact on stockouts. Output: JSON with supplier_id, lead_time_mean, lead_time_std, stockout_risk.
33. Price competitiveness map: Role: Market analyst. Task: Compare listing price vs top competitors by category and sentiment. Output: CSV with category, own_price, competitor_mean, price_gap, sentiment_trend.
34. Ad creative performance: Role: Creative analyst. Task: Rank ad creatives by incremental sales and engagement over last 45 days. Output: JSON with creative_id, incremental_sales, ctr, cvr, roi.
35. WMS accuracy check: Role: Warehouse ops. Task: Validate WMS picks vs shipments and reconcile discrepancies. Output: CSV with shipment_id, picks, discrepancies, adjust_factor.
36. Currency impact analysis: Role: Finance analyst. Task: Assess impact of fx fluctuations on international sales and margins. Output: JSON with currency, revenue_usd, margin_usd, impact_pct.
37. Product page sentiment: Role: Content analyst. Task: Analyze product page reviews sentiment and map to rating distribution. Output: JSON with asin, avg_sentiment, rating_breakdown.
38. Fulfillment error log: Role: Ops. Task: Compile fulfillment error categories and frequency over last 90 days. Output: CSV with error_code, count, last_seen, recommended_fix.
39. Expense category forecast: Role: Controller. Task: Forecast operating expenses by category for next quarter. Output: JSON with category, forecast, confidence.
40. Top rising products: Role: Market analyst. Task: Identify top rising products by velocity and revenue over last 60 days. Output: CSV with sku, revenue, units_sold, velocity.
41. Seasonality scoring: Role: Analytics. Task: Score seasonality strength by category and month. Output: JSON with category, month, seasonality_score.
42. Advertising mix optimizer: Role: Marketing ops. Task: Propose optimal ad mix by channel under budget constraint to maximize revenue. Output: CSV with channel, allocated_budget, projected_revenue.
43. SKU cannibalization analysis: Role: Product analytics. Task: Detect cannibalization between similar SKUs and suggest diversification actions. Output: JSON with sku_pair, cannibalization_score, recommended_action.
44. Customer churn risk: Role: CRM. Task: Identify customers at high risk of churn using purchase recency and frequency. Output: JSON with customer_id, risk_score, recommended_engagement.
45. Refund reason breakdown: Role: Customer support. Task: Break down refunds by reason and correlate with product category. Output: CSV with sku, reason, refunds, refund_rate.
46. Delivery SLA dashboard: Role: Logistics. Task: Build SLA compliance dashboard by carrier and region. Output: JSON with carrier, region, on_time_delivery_rate, avg_delivery_time.
47. New vs returning customers: Role: Analytics. Task: Compare revenue and orders from new vs returning customers for the last 6 months. Output: CSV with segment, revenue, orders, avg_order_value.
48. Gross margin by channel: Role: Finance. Task: Compute gross margin by channel (Amazon store, Facebook, etc.) for last fiscal quarter. Output: JSON with channel, revenue, cogs, gross_margin, margin_pct.
49. Cost per acquisition: Role: Marketing. Task: Calculate CPA by campaign across channels and identify the most cost-effective channels. Output: CSV with campaign_id, channel, cost_per_acquisition, conversions.
50. Inventory forecast vs sales: Role: Demand planner. Task: Compare 6-week inventory forecast with projected sales and flag gaps. Output: JSON with sku, forecast_qty, projected_sales, gap.
51. Product mix optimization: Role: Strategy. Task: Recommend optimal product mix to maximize quarterly gross profit given constraints. Output: JSON with sku, recommended_share, projected_profit.
52. Refund risk by product: Role: Quality. Task: Identify products with high refund risk and suggest quality improvements. Output: JSON with sku, refund_rate, risk_factors, recommended_actions.
53. Ad impression share: Role: PPC. Task: Report impression share by campaign and identify lost opportunities. Output: CSV with campaign_id, impressions, share, lost_opportunities.
54. Vendor scorecard trend: Role: Procurement. Task: Track vendor scorecard over time and alert on downward trends. Output: JSON with vendor_id, score, trend, action_required.
55. Product lifecycle stage: Role: Product analytics. Task: Classify each SKU into lifecycle stage and forecast next stage. Output: CSV with sku, stage, days_in_stage, forecast_transition.
56. Pricing elasticity matrix: Role: Pricing. Task: Build elasticity matrix by price band and demand segment. Output: JSON with price_band, demand_segment, elasticity.
57. Campaign pacing forecast: Role: Marketing. Task: Forecast campaign pacing to stay within quarterly spend while hitting revenue goals. Output: CSV with day, planned_spend, actual_spend, variance.
58. Product detail page score: Role: UX analyst. Task: Score product detail pages on conversion potential based on copy, images, bullets, and reviews. Output: JSON with asin, score, components.
59. Frustration signals: Role: Support ops. Task: Identify top frustration signals from customer messages and categorize by product. Output: JSON with product, signal, frequency.
60. Shipping time benchmarks: Role: Logistics. Task: Benchmark shipping times against industry benchmarks for major regions. Output: CSV with region, avg_time, benchmark_time, delta.
61. Defect rate by batch: Role: QA. Task: Track defect rate by batch for supplier quality checks. Output: JSON with batch_id, defects, total, defect_rate.
62. Promo uplift checklist: Role: Marketing. Task: Create a 10-point checklist to maximize promo uplift for launches. Output: JSON with item, owner, deadline, success_metric.
63. Channel ROI comparison: Role: Analytics. Task: Compare ROI by channel over last two quarters. Output: CSV with channel, revenue, cost, roi.
64. Product ranking forecast: Role: Strategy. Task: Forecast product ranking changes based on price, reviews, and demand signals. Output: JSON with asin, forecast_rank, confidence.
65. Returns by region: Role: Returns team. Task: Summarize returns by region and identify regional trends. Output: JSON with region, returns, return_rate.
66. Offer health overview: Role: Promotions. Task: Assess health of promotional offers across SKUs and suggest consolidation. Output: CSV with sku, offers_active, performance_metric.
67. Cost center dashboards: Role: Controller. Task: Build cost center dashboards by department for last quarter. Output: JSON with department, expenses, variances.
68. Review sentiment drift: Role: Content. Task: Detect drift in review sentiment over time and map to product changes. Output: JSON with asin, sentiment_trend, related_changes.
69. Inventory reserve levels: Role: Inventory. Task: Propose reserve levels by SKU to cover forecast errors. Output: JSON with sku, reserve_qty, rationale.
70. Campaign risk flag: Role: Marketing. Task: Flag campaigns with elevated risk based on multiple metrics and propose mitigations. Output: JSON with campaign_id, risk_score, mitigations.
71. LTV to CAC ratio: Role: Growth. Task: Calculate LTV to CAC ratio by cohort and report actionable insights. Output: JSON with cohort, ltv, cac, ratio.
72. Refund impact on margin: Role: Finance. Task: Assess how refunds affect margin by product and propose pricing adjustments. Output: JSON with sku, margin_before, margin_after_refund, impact.
73. Ad bid optimization: Role: PPC strategist. Task: Recommend bid adjustments by keyword to maximize incremental revenue within budget. Output: CSV with keyword, suggested_bid, projected_revenue.
74. Stockout risk matrix: Role: Supply chain. Task: Build a stockout risk matrix by SKU and supplier. Output: JSON with sku, supplier_id, risk_score, action.
75. Listing optimization prompts: Role: Listing creator. Task: Provide a 7-step prompt series to optimize title, bullets, and images for conversion. Output: JSON with step, instruction, data_needed.
76. Credit note management: Role: Finance. Task: Track credit notes and apply to future orders to minimize revenue leakage. Output: JSON with credit_id, amount_due, applied_to_order.
77. AOV uplift plan: Role: Marketing. Task: Propose tactics to raise average order value with bundles and cross-sells. Output: CSV with tactic, expected_uplift, risk.
78. Fulfillment cost map: Role: Operations. Task: Map fulfillment costs by region and identify savings opportunities. Output: JSON with region, cost_per_order, savings_opportunity.
79. Inventory safety stock: Role: Demand planning. Task: Calculate safety stock per SKU using service level and demand volatility. Output: JSON with sku, safety_stock.
80. Pricing parity check: Role: Compliance. Task: Ensure pricing parity across marketplaces and report deviations. Output: CSV with marketplace, asin, price, parity_status.
81. Campaign freshness score: Role: Marketing. Task: Score campaigns on freshness and novelty to avoid ad fatigue. Output: JSON with campaign_id, score, rationale.
82. Product risk alert: Role: Risk manager. Task: Flag products at risk of stockouts or delisting with recommended actions. Output: JSON with sku, risk, action.
83. Chargeback analysis: Role: Finance. Task: Analyze chargebacks by reason and correlate with fulfillment metrics. Output: CSV with reason, count, impact.
84. Aging accounts receivable: Role: Treasury. Task: List overdue accounts receivable and recommended follow-up. Output: JSON with customer_id, days_overdue, amount_due, action.
85. Product review loop: Role: Product owner. Task: Create a loop to convert reviews into product improvements with a 4-week cadence. Output: JSON with improvement_id, sku, action, due_date.
86. Shipping cost sensitivity: Role: Logistics. Task: Model shipping cost sensitivity to package size and weight. Output: JSON with size_band, weight_band, cost_change.
87. Coupon performance by tier: Role: Promotions. Task: Compare coupon performance across tiers and suggest tier optimization. Output: CSV with tier, usage, revenue, redemption_rate.
88. Delivery time variance: Role: Ops. Task: Analyze variance in delivery times by carrier and reason codes. Output: JSON with carrier, variance_days, common_reasons.
89. Shelf-life risk assessment: Role: Quality. Task: Assess risk of perishable SKU expiry and plan liquidation or promo. Output: JSON with sku, days_to_expiry, risk_score.
90. Inventory correction prompts: Role: Inventory. Task: Create prompts to detect and correct inventory discrepancies between systems. Output: JSON with discrepancy_id, sku, delta, recommended_fix.
91. New customer funnel: Role: Growth. Task: Map new customer journey from acquisition to first purchase and identify drop-offs. Output: JSON with stage, drop_off_rate.
92. Profit by region: Role: Finance. Task: Calculate profit by region and highlight best and worst regions. Output: CSV with region, profit, margin_pct.
93. Ad creative test plan: Role: Marketing. Task: Define a 2-week test plan for ad creatives with metrics and decision criteria. Output: JSON with test_id, variant, metric, decision_criteria.
94. Vendor delivery reliability: Role: Procurement. Task: Measure vendor delivery reliability and alert on supply risk. Output: JSON with vendor_id, on_time_rate, risk_flags.
95. SKU split impact: Role: Finance. Task: Analyze impact of splitting bundles into individual SKUs on revenue and margin. Output: JSON with bundle_id, impact, recommended_action.
96. Campaign KPI snapshot: Role: Marketing. Task: Provide a snapshot of key campaign KPIs: CTR, conversion rate, ACoS, ROAS, revenue. Output: JSON with campaign_id, kpis.
97. Lifecycle email prompts: Role: CRM. Task: Draft 5 lifecycle email prompts tuned for reactivation and retention with CTAs. Output: JSON with email_id, subject, body, call_to_action.
98. Inventory optimization heuristics: Role: Inventory. Task: Apply heuristics to optimize reorder points and safety stock. Output: JSON with sku, reorder_point, safety_stock, justification.
99. A/B test design prompts: Role: Experiment lead. Task: Create a 4-step plan to design A/B tests for product pages, including hypotheses and success criteria. Output: JSON with step, hypothesis, metric, sample_size.
100. Executive KPI dashboard summary: Role: Executive assistant. Task: Produce a concise KPI dashboard description for executives covering revenue, margin, inventory, and ads, plus 3 topline insights. Output: JSON with sections and insights.

Best Practices

• Keep prompts role specific to avoid ambiguous outputs.
• Annotate outputs with clear definitions of KPIs used.
• Test prompts on a small data sample before full scale.
• Combine prompts into a dashboard workflow with scheduled runs.
• Review outputs for data integrity and edge cases.

Common Mistakes to Avoid

• Asking for outputs without defining data sources or fields.
• Using vague KPI targets without numeric thresholds.
• Overloading prompts with too many goals in one run.
• Ignoring data quality and freshness in inputs.
• Not validating outputs against known benchmarks.

FAQ

What is a KPI dashboard for Amazon sellers?

A KPI dashboard summarizes sales, profitability, inventory, and ads metrics to help you monitor performance and make data driven decisions.

How many prompts should I run daily?

Start with a core set of 6 to 12 prompts and expand as you validate outputs, then schedule regular refreshes.

Can these prompts be used for multiple marketplaces?

Yes, adapt the region or marketplace fields in the data inputs and thresholds to fit different marketplaces.

What formats should outputs be in?

Use JSON for structured data and CSV for tabular dashboards; specify the required format in each prompt.

How do I ensure data accuracy?

Feed clean, deduplicated data and verify totals, margins, and KPI targets against known benchmarks.

Can I reuse prompts for other e commerce platforms?

You can adapt the prompts to other platforms by changing data fields to reflect the target platform metrics.