ABC Analysis for Shopify: Which SKUs Deserve Your Attention and Cash

ABC analysis divides your entire catalog into three tiers based on each SKU's share of total revenue, so you know exactly where to concentrate your reorder budget, safety stock, and attention. In most Shopify stores, roughly 20% of SKUs generate around 70-80% of revenue, while the bottom 50% of SKUs contribute only about 5%. Running the analysis takes one export and a spreadsheet, but acting on it correctly for each tier is where most merchants leave money on the table.

Key takeaways

• A-items (top ~20% of SKUs, ~70-80% of revenue): highest priority, zero tolerance for stockouts, high safety stock.
• B-items (next ~30% of SKUs, ~15% of revenue): standard management, review monthly, candidate items that can drift up or down.
• C-items (bottom ~50% of SKUs, ~5% of revenue): tightly controlled replenishment, flag for dead-stock review before every reorder.
• Classifying by revenue alone misses demand volatility. Layering XYZ analysis on top reveals which A-items are also unpredictable, the most expensive SKUs to manage.
• Re-run the analysis at least quarterly. A product classified as B last quarter can shift to A after a single viral moment or seasonal spike.

The exact formula, step by step

You do not need special software to run your first ABC analysis. Here is the manual method using a Shopify data export:

1. Export your Sales by Product report from Shopify Admin (Analytics > Reports > Sales by product). Use a rolling 90 or 365 days, depending on your catalog's seasonality.
2. Add a revenue column per SKU: units sold multiplied by selling price. If margin data is available, use gross margin instead, since revenue can be misleading when COGS varies widely across your catalog.
3. Sort descending by revenue (or margin) and add a cumulative percentage column.
4. Apply thresholds: assign A where cumulative % reaches 0-75%, B from 75-92%, C from 92-100%. Some practitioners use 80/95/100; the exact split matters less than consistency across runs.
5. Tag your SKUs in a master sheet or your inventory app so every reorder decision starts from the right tier.

For a formula shorthand: annual consumption value per item = unit cost x annual units sold. Sort descending, compute running total, divide each row's running total by the grand total, and assign A/B/C at your chosen thresholds.

What to do differently for each tier

The classification is worthless unless it changes your behavior. Here is the differentiated policy that supply chain teams use:

For A-items specifically:

• Set a reorder point based on lead time demand plus a safety stock buffer. Never reorder by feel.
• Keep at least one backup supplier on record for your top 10 A-items.
• Review stock levels weekly, not monthly.
• Calculate the cost of a single stockout day: average daily units sold x gross margin per unit. For a SKU doing $500/day at 40% margin, one week out of stock costs $1,400 in lost gross profit, far more than any forecasting tool subscription.

For C-items specifically:

• Before every reorder, ask: has this SKU sold in the last 90 days? If not, it is a dead-stock candidate.
• Do not tie up cash in C-items "just in case." Their low revenue contribution means a stockout costs almost nothing, while overstocking costs real warehouse space and working capital.
• Consider running a clearance promotion on C-items before they reach the 180-day-no-movement threshold, the point at which most buyers write them off.

Why pure ABC misses part of the picture (and how to fix it)

ABC ranks SKUs by value but says nothing about how predictably they sell. A product can be a high-revenue A-item and still have wildly erratic weekly demand, making it expensive to hold and hard to forecast.

That is where XYZ analysis layers in. XYZ classifies SKUs by demand variability:

• X-items: stable, predictable demand. Low coefficient of variation. Easy to forecast, order frequently, minimal safety stock needed.
• Y-items: moderate variability, often seasonal. Require statistical forecasting and reasonable safety stock buffers.
• Z-items: erratic, unpredictable demand. High coefficient of variation. Require either generous safety stock or explicit acceptance that stockouts will occur.

Combining both frameworks creates a 9-cell matrix. The most critical cell is A-Z: high revenue, unpredictable demand. These SKUs deserve your most sophisticated reorder logic and the largest safety stock relative to their lead time. An A-X item (high value, steady demand) can actually be managed with tighter stock because you can forecast it with confidence.

For most Shopify merchants managing under 1,000 SKUs, just knowing which of your A-items are also Z-items is enough to prevent the majority of painful, margin-destroying stockouts.

The most common ABC mistakes on Shopify

Even merchants who run the analysis correctly often make the same downstream errors:

• Running it once and forgetting it. A product classified as C last month may have shifted to A after a TikTok mention or a seasonal peak. Classifications go stale within a quarter for most catalogs.
• Using units sold instead of revenue (or margin). A high-volume, low-price SKU looks like an A-item by unit count but may be a C-item by margin contribution. Always tie the analysis to financial impact.
• Applying uniform reorder rules across all tiers. If your reorder point formula is the same for A-items and C-items, you are either overinvesting in C-items or underprotecting your A-items.
• Ignoring new SKUs. A product launched 30 days ago has no history. Treat new launches as provisional B-items until you have at least 60-90 days of data.
• Not connecting ABC tier to purchase order priority. Knowing your tier structure is useless if your POs do not reflect it. Your A-item suppliers should always be ordered first when cash is tight.

How to turn ABC classifications into daily reorder decisions

The gap between running an ABC analysis and actually acting on it every day is where most merchants stall. A quarterly spreadsheet exercise only helps if someone checks it before every reorder. That stops being practical once you pass a few hundred SKUs or manage multiple locations.

This is where Stockcast: Inventory Forecast fits into the workflow. It monitors your Shopify stock levels daily, ranks reorder recommendations by urgency, and shows the math behind every suggestion so you can see exactly which SKUs are A-items burning through safety stock fastest. Every stockout prediction comes with a transparent calculation, not just a colored alert, so your buying decisions are grounded in the same logic you would build in a spreadsheet, just without the manual rebuild every week.

For Shopify merchants migrating off Stocky (which shut down August 31, 2026), you can import your existing supplier CSV data directly and have your supplier and tier history intact from day one.

Re-run your ABC analysis on this schedule

• Quarterly (minimum): full catalog re-classification by rolling 90-day revenue.
• Monthly: spot-check your top 20 A-items for velocity changes and any new entrants that might be climbing toward A-tier.
• After any major event: a sale, a viral moment, a new product launch, or a supplier disruption should all trigger a manual review of affected SKUs.
• Pre-season: if your business is seasonal, run ABC on last year's same-quarter data before ordering for the upcoming peak, not on an annual average that will underweight the seasonal spike.

Try Stockcast: Inventory Forecast on the Shopify App Store to turn your ABC tiers into ranked, daily reorder decisions with no spreadsheet maintenance required.