100 Best Claude Excel Data Analysis Prompts for Etsy Sellers

Direct Answer

The best Claude prompts for Excel data analysis for Etsy sellers are a practical, ready-to-use library of 100 prompts that cover sales trends, pricing, inventory, campaigns, and profitability. Each prompt provides role, task, context placeholders, output format, and constraints to produce actionable results in Excel. Use them to standardize analysis and accelerate decision making.

Introduction

This page is a practical prompt library for Excel data analysis tailored to Etsy sellers. It helps you turn raw Etsy data into clear, actionable insights in Excel.

Designed for shop owners, managers, and analysts, these Claude prompts guide you to diagnose performance, optimize pricing, and forecast demand with consistent, repeatable workflows.

How to Use These Claude Prompts

• Replace placeholders like [listing_id], [category], and [week] with your actual data columns before running the prompt.
• Add constraints and success criteria to force the output into a structured, ready-to-import format for Excel.
• Ask for a specific output format such as a table, CSV-ready data, or a pivot-ready structure and include a brief interpretation.
• Request validation steps to check the results against historical data or a holdout sample.
• If needed, combine prompts in a sequence to build a complete analysis stack from data import to insights.
• When sharing with a team, export the results as CSV and attach a short executive summary.

100 Best Claude Excel Data Analysis Prompts for Etsy Sellers

1. Sales trend overview: You are an analytics assistant. Task: Generate a 12-week sales trend summary for an Etsy shop using an Excel workbook with sheets: Data, Metrics, and Insights. Context: The shop sells handmade jewelry. Data placeholders: [weekly_sales], [week], [category]. Output format: numbered bullet list with weekly totals, moving averages, and a chart-ready data table. Constraints: include at least two visual-ready series and highlight any upward or downward shifts.
2. Top-selling items by category: Role: Data analyst. Task: List top-selling product categories for the last 90 days using Excel data: [category], [units_sold], [revenue], [date]. Output: a ranked table with category, total units, total revenue, average price, and a brief interpretation paragraph for the top 3 categories.
3. Pricing elasticity check: You are an analyst. Task: Assess price sensitivity for a product line by simulating price changes in Excel. Use columns: [current_price], [price_change], [estimated_sales_change], [profit] over a 60-day period. Output: a table of scenarios and a recommendations section.
4. Inventory turnover streaks: Role: Inventory analyst. Task: Calculate monthly inventory turnover for the last 12 months. Data: [month], [cost_of_goods_sold], [average_inventory]. Output: turnover rate, days in inventory, and flags for high risk stock levels.
5. Listing performance heatmap: You are a data viz helper. Task: Create an Excel-ready heatmap of listing performance by tag and season. Data: [listing_id], [tag], [season], [views], [favorites], [orders]. Output: instructions to generate conditional formatting rules and a summary interpretation.
6. Revenue by audience: Role: Marketing data analyst. Task: Break down revenue by audience segments in the last 6 months using columns: [date], [audience], [revenue]. Output: a pivot-ready table plus a narrative on which audience drives growth.
7. COGS vs price optimization: You are an optimization specialist. Task: Build a model in Excel to balance cost of goods sold and price to maximize gross margin for a product group. Data: [cost], [price], [units_sold], [season]. Output: a scenario table and recommended price range.
8. Gross margin by product: Role: Financial analyst. Task: Compute gross margin per product over the last quarter. Data: [product], [revenue], [cost_of_goods_sold]. Output: table with margin %, rank, and a brief takeaway.
9. Demand forecasting baseline: You are a forecasting assistant. Task: Create a baseline forecast in Excel for next 8 weeks using historical weekly sales [week], [sales]. Output: forecasted values, confidence interval, and a short plan for validation.
10. Seasonality decomposition: Role: Data scientist. Task: Decompose seasonality in sales data for Etsy shop. Data: [week], [sales]. Output: seasonal indices, trend line, and actionable insights for stock planning.
11. Profitability by listing: You are a profitability analyst. Task: Calculate profit per listing over last 12 weeks using columns: [listing_id], [revenue], [cost]. Output: list of top performers and recommendations to improve underperformers.
12. Customer lifetime value: Role: CRM analyst. Task: Estimate customer lifetime value by cohort in Excel. Data: [customer_id], [order_date], [order_value], [repeat_purchase]. Output: CLV per cohort and strategic actions.
13. Refund impact analysis: You are an operations analyst. Task: Measure impact of refunds on monthly profit. Data: [month], [refunds], [net_sales], [refund_rate]. Output: impact report and mitigation ideas.
14. Forecast accuracy check: Role: QA reviewer. Task: Compare actuals vs forecast for last 12 weeks. Output: error metrics, bias check, and action plan to improve forecasting in Excel.
15. A/B test results synthesis: You are a data integrator. Task: Consolidate A/B test results for product images into a single dashboard. Data: [test_id], [variant], [metric], [value]. Output: concise conclusions and next steps.
16. Price ladder mapping: Role: Pricing strategist. Task: Create a price ladder for a suite of products with cross-sell potential. Data: [product], [base_price], [elasticity], [bundle_revenue]. Output: ladder with recommended price tiers.
17. Stockout risk indicators: You are an inventory risk analyst. Task: Identify products at risk of stockouts in the next 4 weeks. Data: [listing_id], [stock], [lead_time], [sales_rate]. Output: risk flags and replenishment suggestions.
18. Discount impact tracker: Role: Promotions analyst. Task: Measure effect of discounts on revenue and gross margin. Data: [discount], [revenue_before], [revenue_after], [gross_margin_before], [gross_margin_after]. Output: impact summary and guidance.
19. Refund recoverability: You are a financial recovery analyst. Task: Estimate percentage of refunds that can be recovered through exchanges or credits. Data: [refund_id], [status], [credit_possible]. Output: recovery rate and recommended policy changes.
20. Product mix optimization: Role: Category analyst. Task: Optimize product mix for profitability. Data: [product], [units_sold], [revenue], [cost]. Output: recommended mix adjustments and priority listings.
21. Seasonal stock plan: You are an planning analyst. Task: Create a seasonal stock plan for upcoming holidays. Data: [month], [historical_sales], [lead_time], [safety_stock]. Output: plan with order quantities and timing.
22. Customer churn predictors: Role: CRM analyst. Task: Build a churn risk score for customers using Excel. Data: [customer_id], [last_purchase_days], [total_spent], [visits]. Output: risk scores and retention actions.
23. Return rate analysis: You are an operations analyst. Task: Analyze product return rates by listing. Data: [listing_id], [returns], [orders], [reason]. Output: table of rates and improvement ideas.
24. Listing performance benchmarks: Role: Competitor analyst. Task: Create benchmarks for listing performance compared to top sellers. Data: [listing_id], [views], [likes], [orders]. Output: benchmark table and optimization tips.
25. Pricing scenario comparison: You are a pricing analyst. Task: Compare three pricing scenarios for a product line across 8 weeks. Data: [scenario], [price], [units_sold], [revenue]. Output: side-by-side table and recommendation.
26. Profit per channel: Role: Channel analyst. Task: Compute profit by sales channel (direct, marketplace) over last quarter. Data: [channel], [revenue], [cost], [quantity]. Output: table and insights.
27. Inventory aging report: You are an inventory specialist. Task: Generate aging report for inventory over 180 days. Data: [listing_id], [days_in_inventory], [cost]. Output: aging buckets and actions.
28. SEO impact on sales: Role: SEO analyst. Task: Correlate listing SEO metrics with sales. Data: [listing_id], [search_rank], [views], [orders]. Output: correlation results and optimization ideas.
29. Bundle profitability: You are a product analyst. Task: Assess profitability of bundles versus individual items. Data: [bundle_id], [bundle_price], [bundle_cost], [units_sold]. Output: profitability comparison and recommendations.
30. Customer segment heatmap: Role: Marketing data scientist. Task: Create a heatmap of revenue by customer segment and month. Data: [segment], [month], [revenue]. Output: heatmap-ready data and segment insights.
31. Churn reduction plan: You are a CRM strategist. Task: Propose a 90-day churn reduction plan with Excel-ready metrics. Data: [customer_id], [days_since_last_purchase], [lifetime_value]. Output: actions, owners, and KPIs.
32. Inventory safety stock: Role: Operations analyst. Task: Compute safety stock levels for high-variance items. Data: [item], [demand_variability], [lead_time], [service_level]. Output: safety stock numbers and rationale.
33. COGS optimization checklist: You are a cost optimization manager. Task: Create a checklist to reduce cost of goods sold without compromising quality. Data: [supplier], [cost], [quality]. Output: 12-step checklist.
34. Sales funnel leakage: Role: Growth analyst. Task: Identify where sales drop off in the Etsy funnel using weekly data. Data: [stage], [visits], [conversions], [date]. Output: leakage report and fixes.
35. Aging accounts receivable: You are a finance analyst. Task: Track aging accounts receivable for Etsy payments. Data: [invoice_id], [due_days], [amount_due], [status]. Output: aging summary and collection plan.
36. Listing health score: Role: Quality control analyst. Task: Create a health score per listing based on views, conversion, and returns. Data: [listing_id], [views], [conversions], [returns]. Output: score model and improvement ideas.
37. Pricing fast-followers: You are a pricing researcher. Task: Validate fast-follow price changes against competitors with simple elasticity. Data: [competitor_price], [your_price], [sales_change]. Output: guidance on timing and thresholds.
38. Refund trend analysis: Role: Finance analyst. Task: Detect refund trends by month and product category. Data: [month], [refunds], [category], [orders]. Output: trend chart and policy notes.
39. Product life cycle view: You are a product portfolio analyst. Task: Classify listings by lifecycle stage and suggest actions. Data: [listing_id], [stage], [sales_rate]. Output: portfolio view and next-step plan.
40. Marketing spend efficiency: Role: Marketing analyst. Task: Measure ROI of promotions by listing. Data: [listing_id], [promo_spend], [revenue], [orders]. Output: ROI table and optimization tips.
41. Day-of-week demand: You are a demand planner. Task: Analyze demand patterns by day of week for listings. Data: [listing_id], [day_of_week], [orders]. Output: daily demand table and staffing guidance.
42. Product similarity clustering: Role: Data scientist. Task: Cluster listings by similarity to identify cross-sell opportunities. Data: [listing_id], [tags], [views], [orders]. Output: cluster labels and recommended bundles.
43. Checkout abandonment: You are a UX analyst. Task: Identify reasons for checkout abandonment from data. Data: [listing_id], [abandon_rate], [device], [referrer]. Output: root causes and fixes.
44. Review sentiment impact: Role: Brand analyst. Task: Correlate review sentiment with sales. Data: [listing_id], [average_rating], [sentiment_score], [sales]. Output: correlation and action plan.
45. Inventory replenishment timing: You are an supply planner. Task: Determine optimal replenishment dates for top SKUs. Data: [sku], [lead_time], [current_stock], [sales_rate]. Output: schedule and quantities.
46. Tax and fees optimization: Role: Accountant. Task: Identify opportunities to minimize Etsy fees and tax impact in pricing. Data: [fee_type], [amount], [net_revenue]. Output: savings plan.
47. Seasonal promo calendar: You are a promotions planner. Task: Create a seasonal promo calendar with expected lift. Data: [season], [historical_lift], [duration]. Output: calendar with targets.
48. Warranty and service data: Role: Operations data analyst. Task: Track warranty or service data by listing to inform product quality improvements. Data: [listing_id], [warranty_count], [cost], [satisfaction]. Output: insights and actions.
49. Growth forecast dashboard: You are a dashboard designer. Task: Build a compact forecast dashboard for 12 weeks covering revenue, orders, and inventory. Output: table and chart-ready specs.
50. Bundle cross-sell map: Role: Merchandising analyst. Task: Map cross-sell opportunities between listings to form bundles. Data: [listing_id], [related_ids], [co_purchase_rate]. Output: bundle suggestions and rationale.
51. Price sensitivity by category: You are a pricing strategist. Task: Compare price sensitivity across categories using last 180 days data. Data: [category], [price], [units_sold]. Output: sensitivity table and recommended prices.
52. Lead time variability: Role: Operations analyst. Task: Analyze supplier lead time variability and impact on stockouts. Data: [supplier_id], [lead_time], [variance]. Output: variability report and mitigation plan.
53. Customer acquisition cost: You are a marketing analyst. Task: Compute CAC per channel using Excel. Data: [channel], [spend], [new_customers], [period]. Output: CAC by channel and interpretation.
54. Product return reasons: Role: Product manager. Task: Catalog top reasons for returns from data and propose fixes. Data: [listing_id], [return_reason], [count]. Output: list of fixes with impact estimates.
55. Seasonal revenue map: You are a business analyst. Task: Create a monthly revenue map for the year with seasonality cues. Data: [month], [revenue]. Output: map and action plan.
56. Listing SEO scorecard: Role: SEO analyst. Task: Build an SEO scorecard for listings based on title, tags, and descriptions. Data: [listing_id], [title_score], [tags_score], [description_score]. Output: scorecard and optimization steps.
57. Currency and fees audit: You are an finance auditor. Task: Audit currency conversions and Etsy fees for accuracy. Data: [order_id], [currency_rate], [fee]. Output: audit findings and fixes.
58. Customer segmentation by value: Role: CRM strategist. Task: Segment customers by value and engagement. Data: [customer_id], [lifetime_value], [orders], [recency]. Output: segments and targeting plan.
59. Product life cycle actions: You are a product manager. Task: Propose actions per lifecycle stage for listings. Data: [listing_id], [stage], [sales_rate]. Output: actions and KPIs.
60. Churn-safe promotions: Role: Retention specialist. Task: Design promotions that minimize churn while improving LTV. Data: [customer_id], [recency], [lifetime_value]. Output: promo ideas and thresholds.
61. Aged inventory cleanup: You are an operations planner. Task: Create a plan to clear aged inventory via discounts or bundles. Data: [listing_id], [days_old], [cost]. Output: plan with targets.
62. Export automation checklist: Role: Automation consultant. Task: Create an Excel-friendly export checklist to standardize data pipelines from Etsy. Data: none. Output: step-by-step checklist.
63. Validation of data sources: You are a data governance advisor. Task: Validate data quality for Etsy sales dataset. Data: [source], [accuracy], [consistency]. Output: validation results and fixes.
64. Anomaly detection rules: Role: Data quality engineer. Task: Create rules to detect anomalies in weekly sales. Data: [week], [sales]. Output: thresholds and alert plan.
65. Markdown rendering test: You are a content quality tester. Task: Ensure Excel exports render correctly in Markdown previews. Data: none. Output: checklist and example snippets.
66. Data dictionary starter: Role: Data manager. Task: Produce a starter data dictionary for Etsy sales dataset. Data: none. Output: field list with definitions.
67. Dockable data templates: You are a template designer. Task: Provide Excel-ready templates for common Etsy analyses. Data: none. Output: template descriptions and column schemas.
68. Cross-channel revenue view: Role: BI analyst. Task: Combine Etsy and external sales into a single Excel view. Data: [platform], [orders], [revenue]. Output: unified table and reconciliation notes.
69. Forecast bias fix plan: You are a forecasting engineer. Task: Identify and fix sources of bias in sales forecasts. Data: [week], [forecast], [actual]. Output: bias analysis and corrective steps.
70. Promotions lift attribution: Role: Analytics lead. Task: Attribute revenue lifts to specific promotions within Excel. Data: [promo], [revenue_with_promo], [revenue_without]. Output: uplift table and caveats.
71. Cost-saving supplier review: You are a procurement analyst. Task: Compare suppliers to reduce costs without quality loss. Data: [supplier], [cost], [rating]. Output: ranking and negotiation notes.
72. Customer feedback loop: Role: Experience designer. Task: Map feedback to product improvements in Excel. Data: [feedback_id], [rating], [topic]. Output: priorities and owner assignments.
73. Product ranking by ROI: You are a portfolio analyst. Task: Rank listings by ROI over last 6 months. Data: [listing_id], [revenue], [cost], [period]. Output: ordered list and actions.
74. Item-level lag analysis: Role: Analytics engineer. Task: Compute lag between listing views and orders. Data: [listing_id], [views], [orders], [lag_days]. Output: lag matrix and interpretation.
75. NLP review insights: You are a data scientist. Task: Extract themes from reviews to guide product updates. Data: [listing_id], [reviews_text]. Output: theme list and recommended actions.
76. Checkout optimization prompts: Role: UX strategist. Task: Propose prompts for optimizing checkout flow in Etsy listings. Data: none. Output: prompts and expected outcomes.
77. Returns forecast model: You are a forecasting analyst. Task: Build a model predicting returns by listing. Data: [listing_id], [season], [past_returns]. Output: forecast and mitigation plan.
78. Pricing parity check: Role: Compliance analyst. Task: Ensure pricing parity across variants and marketplaces. Data: [listing_id], [price], [market]. Output: parity report and fixes.
79. Promotions risk assessment: You are a risk manager. Task: Assess risk of promotions eroding margin long-term. Data: [promo], [margin_before], [margin_after]. Output: risk rating and controls.
80. SKU rationalization: Role: Merchandising lead. Task: Propose SKU removals or consolidations to improve profitability. Data: [sku], [units_sold], [margin]. Output: rationalization plan.
81. Tag performance audit: You are an SEO auditor. Task: Audit listing tags for search performance. Data: [listing_id], [tags], [views], [orders]. Output: tag performance report and tweaks.
82. Delivery times impact: Role: Ops analyst. Task: Correlate delivery times with satisfaction and repeat purchases. Data: [order_id], [delivery_days], [repeat_purchase]. Output: correlation and improvement ideas.
83. Currency effects report: You are a finance analyst. Task: Analyze how currency fluctuations affect revenue in international Etsy sales. Data: [currency], [revenue], [exchange_rate]. Output: impact summary and hedging notes.
84. Image quality correlation: Role: Creative analyst. Task: Explore correlation between image quality scores and conversions. Data: [listing_id], [image_score], [conversions]. Output: correlation and creative recommendations.
85. Content harvest plan: You are a content strategist. Task: Plan content pieces to support top-performing listings. Data: [listing_id], [top_words], [traffic]. Output: content map and calendar.
86. Inventory skew analysis: Role: Inventory analyst. Task: Detect skew in inventory by listing vs demand. Data: [listing_id], [stock], [demand]. Output: skew report and adjustment steps.
87. Profitability guardrails: You are a finance ops lead. Task: Set profitability guardrails per category in Excel. Data: [category], [margin], [threshold]. Output: guardrails and alerts.
88. Seasonal projection drill: Role: Planner. Task: Create a drill-down seasonal projection for peak months. Data: [month], [historical], [variance]. Output: projection table and plan.
89. Batch analysis prompts: You are a data coach. Task: Provide prompts to batch analyze multiple listings efficiently in Excel. Data: [listing_ids], [metrics]. Output: batch analysis prompts.
90. Vendor performance matrix: Role: Procurement analyst. Task: Build a matrix comparing vendors on cost, delivery, quality. Data: [vendor], [cost], [delivery], [quality]. Output: matrix and action plan.
91. Sales by currency zone: You are a market analyst. Task: Break down sales by currency zone for Etsy shop. Data: [zone], [revenue], [orders]. Output: zone table and insights.
92. Discount sizing guide: Role: Pricing strategist. Task: Create a guide for discount depths by product category. Data: [category], [cost], [current_discount]. Output: tiered discounts and rationale.
93. User journey mapping: You are a CX analyst. Task: Map customer journey from listing view to purchase in Excel. Data: [listing_id], [stage], [time_to_purchase]. Output: journey map and gaps.
94. Stock-to-sales ratio: Role: Inventory planner. Task: Compute stock-to-sales ratio per listing. Data: [listing_id], [stock], [sales]. Output: ratio table and reorder signals.
95. Seasonality buffer plan: You are a planning analyst. Task: Create a buffer stock plan for peak season. Data: [month], [forecast_demand], [lead_time]. Output: buffer quantities and timing.
96. Cost center analysis: Role: Accountant. Task: Allocate Etsy costs to product groups for accurate margins. Data: [cost_center], [cost], [revenue]. Output: margins by center.
97. Image-driven conversion: You are a conversion analyst. Task: Analyze how image order affects conversions and propose prompts for improvement. Data: [listing_id], [image_order], [conversions]. Output: findings and prompts.
98. Return prevention prompts: Role: Operations planner. Task: List prompts to reduce returns without harming sales. Data: [listing_id], [return_rate], [root_cause]. Output: actionable prompts.
99. Dashboard storytelling: You are a data storyteller. Task: Build a compact Excel dashboard narrative for Etsy profitability. Data: [revenue], [cost], [orders]. Output: dashboard structure and captions.
100. Data clean room setup: Role: Data engineer. Task: Propose a clean data room setup for Etsy sales analytics in Excel. Data: none. Output: schema, permissions, and file naming conventions.

Best Practices

• Keep data clean and consistently formatted before running prompts to improve accuracy.
• Export results in a stable format (CSV or XLSX) to avoid parsing issues.
• Reuse prompts with the exact same placeholders to maintain comparability across analyses.
• Annotate outputs with a brief interpretation to speed up decision making.
• Guard sensitive data by masking personal information when sharing prompts results.

Common Mistakes to Avoid

• Using vague prompts without specific data fields or time frames, leading to ambiguous results.
• Ignoring data quality or freshness, which yields misleading conclusions.
• Forgetting to specify output formats, causing hard-to-use results.
• Overcomplicating prompts with excessive constraints that block useful insights.
• Not validating outputs against historical data or business context.

FAQ

What is the purpose of these Claude prompts for Etsy data analysis in Excel?

They provide ready-to-run instructions that produce structured Excel outputs for sales, pricing, inventory, and campaigns.

Do I need to customize placeholders for my shop?

Yes, replace placeholders like [week], [listing_id], and [category] with your actual data columns.

Can these prompts be used for any Etsy shop size?

Yes, they scale from small shops to larger stores by adjusting data ranges and time windows.

How should I verify prompt outputs in Excel?

Cross-check totals, run simple sanity checks, and compare against known benchmarks or holdout periods.

Which prompts are best for seasonal planning?

Prompts focused on seasonality decomposition, seasonal stock plans, and revenue maps are particularly useful.

How do I keep prompts safe and compliant?

Avoid sharing sensitive customer data, mask identifiers, and only export aggregated results when necessary.