1
Key Concepts
ABC analysis classifies inventory into three tiers based on revenue contribution: A-items (typically the top 10-20% of SKUs by revenue, deserving the tightest stock monitoring and forecasting attention), B-items (a moderate middle tier, monitored less intensively), and C-items (the long tail of low-revenue SKUs, often the majority of your catalog by count but a small fraction of revenue, suitable for simpler, less frequent review). This classification lets you allocate limited operational attention where it actually matters most.
2
Best Practices
Recalculate your ABC classification periodically (quarterly is reasonable for most sellers), since which SKUs fall into which tier shifts as sales patterns change. Apply tighter safety stock and more frequent reorder review to A-items specifically — a stockout on an A-item costs far more in lost revenue than the same stockout on a C-item. Don't ignore C-items entirely, but review them on a lighter cadence (e.g., monthly or quarterly) rather than spending equal attention across your entire catalog.
3
Implementation
Pull your last 3-6 months of revenue by SKU and rank them — the classic ABC split is roughly 70-80% of revenue from the top ~20% of SKUs (A), a further 15% from the next 30% (B), and remaining revenue spread across the rest (C), though your actual split may vary. Once classified, set your reorder and monitoring cadence to match each tier rather than treating your entire catalog uniformly.
Pro Tip
Spending equal inventory-management attention across your entire catalog wastes effort on C-items and often under-attends your A-items — ABC analysis exists specifically to correct that imbalance.

Key Takeaways
- ABC analysis splits inventory into three tiers by revenue contribution
- A-items (top ~20% of SKUs) deserve the tightest monitoring and stock attention
- C-items can be reviewed on a lighter, less frequent cadence
- Recalculate classification periodically as sales patterns shift
- Match your reorder and monitoring cadence to each tier, not a uniform approach


