Amazon Seller SQL Queries & Database Solutions | AI2SQL

Managing profit, inventory, and analytics as an Amazon Seller means handling massive, complex databases. Manual SQL writing is slow and error-prone—especially when profit analysis or inventory tracking decisions depend on accurate, real-time reporting. AI2sql empowers Amazon Seller teams to generate precise SQL queries using natural language—no coding needed. Instantly surface profit by product, track inventory levels, or monitor KPIs. Save 10+ hours weekly and reduce errors by 95%—all while meeting compliance requirements and boosting ROI.

Common Amazon Seller SQL Query Challenges

• High-volume transaction data—difficult to summarize for profit analysis

• Real-time inventory tracking—requires accurate, up-to-date queries

• Complex fee and commission structures

• Regulatory compliance for data reporting (SOX, PCI, etc.)

• Manual SQL writing leads to inefficiencies & mistakes

Essential Amazon Seller SQL Queries [Live Generator Widget]

Use these ready-to-run examples or Try AI2sql Generator for custom Amazon Seller queries.

-- Profit analysis: Total profit per SKU last month
SELECT sku, SUM(revenue - cost) AS total_profit
FROM sales
WHERE sale_date BETWEEN DATEADD(month, -1, GETDATE()) AND GETDATE()
GROUP BY sku;

-- Low inventory alert: Products below 10 units
SELECT sku, product_name, quantity_in_stock
FROM inventory
WHERE quantity_in_stock < 10;

-- Top selling SKUs by units sold (past 30 days)
SELECT sku, product_name, SUM(quantity_sold) AS units_sold
FROM sales
WHERE sale_date >= DATEADD(day, -30, GETDATE())
GROUP BY sku, product_name
ORDER BY units_sold DESC;

-- Refund rate by product category
SELECT category, COUNT(refund_id) * 100.0 / COUNT(DISTINCT order_id) AS refund_rate_pct
FROM refunds
JOIN products ON refunds.product_id = products.product_id
GROUP BY category;

-- Inventory velocity: Days of inventory left per SKU
SELECT sku, product_name, quantity_in_stock / NULLIF(AVG(daily_sales), 0) AS days_left
FROM (
  SELECT sku, product_name, quantity_in_stock,
    SUM(quantity_sold)/30 AS daily_sales
  FROM sales
  JOIN inventory ON sales.sku = inventory.sku
  WHERE sale_date >= DATEADD(day, -30, GETDATE())
  GROUP BY sku, product_name, quantity_in_stock
) AS t;

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Real-World Amazon Seller SQL Examples

• Analyze gross and net profit by SKU, factoring in Amazon fees

• Track FBA vs. FBM inventory separately for compliance

• Automate daily profit/loss reporting for Amazon Seller Analytics

• Monitor sales spikes by region or fulfillment channel

Generate Amazon Seller queries instantly - $24/month

Why Amazon Seller Professionals Choose AI2SQL

• No SQL expertise needed—generate complex queries from plain English

• Save 10+ hours weekly on reporting and analysis

• Reduce errors by 95% for compliance (SOX, PCI, Amazon Seller policies)

• Track profitability, inventory, and KPIs in real time

• Trusted by 5,000+ Amazon Seller professionals and Fortune 500 teams

Generate Amazon Seller queries instantly - $24/month

Frequently Asked Questions

• How does AI2sql save time for Amazon Seller database analysis?
  AI2sql auto-generates accurate queries from natural language, eliminating manual SQL work for profit analysis and inventory tracking—saving teams 10+ hours weekly.

• Is AI2sql secure and compliant for Amazon Seller data?
  Yes, AI2sql supports best practices to comply with Amazon Seller policies and major regulations like SOX & PCI.

• Can AI2sql handle our high-volume Amazon Seller analytics SQL needs?
  Absolutely—AI2sql is built to support millions of transactions, inventory, and KPI reporting with batch query capabilities.

• What KPIs can we track with AI2sql for Amazon Seller?
  Track profit, fees, units sold, inventory days left, refund rates, and more—all via instant queries.

• Do I need to know SQL to use AI2sql for Amazon Seller reporting?
  No, simply describe your business question and AI2sql handles the SQL.

Amazon Seller Analytics Solutions

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