How to Use ABC Analysis to Prioritize Your Shopify Inventory

Not all SKUs are created equal

If you manage inventory for a Shopify store, you probably treat every SKU the same. You try to keep everything in stock. You order when things look low. You stress out when a slow-moving variant runs out, just like you do when your best seller runs out.

This is a mistake. Treating every SKU equally is the fastest way to tie up your cash flow in dead inventory while simultaneously stocking out of the products that actually pay your bills.

In supply chain operations, there is a framework for fixing this. It is called ABC analysis. It is how enterprise companies decide where to focus their inventory capital, and it works just as well for a 50-SKU Shopify store as it does for a 50,000-SKU warehouse.

The 80/20 rule of inventory

ABC analysis is based on the Pareto principle: roughly 80% of your results come from 20% of your efforts. In ecommerce inventory, this usually means 80% of your revenue comes from 20% of your SKUs.

ABC analysis forces you to categorize your catalog based on revenue contribution:

• A items: The top 20% of your SKUs that generate roughly 80% of your revenue. These are your cash cows.
• B items: The next 30% of your SKUs that generate roughly 15% of your revenue. These are your steady, middle-of-the-pack performers.
• C items: The bottom 50% of your SKUs that generate the last 5% of your revenue. These are your slow movers, niche variants, and accessories.

Once you categorize your SKUs, you stop treating them equally. You apply different rules, different service levels, and different amounts of attention to each group.

How to calculate your ABC categories

You do not need specialized software to do this. You just need your Shopify order data and a spreadsheet.

1. Export your data. Pull the last 90 days of sales data by SKU from Shopify. You need the SKU, the unit price, and the total units sold.
2. Calculate revenue contribution. Multiply units sold by unit price to get total revenue per SKU over that 90-day period.
3. Sort and rank. Sort the list by total revenue, from highest to lowest.
4. Calculate cumulative percentage. Add a column that calculates the running total of revenue as a percentage of your total store revenue.
5. Assign categories. The SKUs that make up the first 80% of cumulative revenue are your A items. The next 15% (from 80% to 95%) are your B items. The remaining SKUs are your C items.

You will likely find that a shockingly small number of SKUs drive the vast majority of your business.

Applying ABC to your inventory strategy

Categorizing your SKUs is only useful if it changes how you manage them. Here is how you apply the ABC framework to the formulas we have covered in previous guides.

Setting service levels

In our guide on how to calculate safety stock, we introduced the concept of a service level: the percentage of time you want to be in stock. Higher service levels require exponentially more safety stock.

If you try to maintain a 99% service level across your entire catalog, you will tie up far more capital than the math justifies. ABC analysis tells you where to spend that capital:

• A items: Target a 95% to 97.5% service level. A stockout here is a real problem. You want deep safety stock buffers.
• B items: Target a 90% to 95% service level. You want to stay in stock, but you can accept a slightly higher risk of a brief stockout to preserve cash.
• C items: Target an 85% to 90% service level. You can afford to stock out of these occasionally. Do not tie up capital buffering slow movers.

The cash-flow-aware ordering strategy

When calculating your Economic Order Quantity (EOQ), ABC analysis helps you make practical adjustments to your order sizes and review frequency. But the right approach is not always obvious, and many operators get it backwards.

The instinct is to order large quantities of your A items because they are important, and small quantities of your C items because they are not. For a cash-conscious operator, this is exactly the wrong move.

A items drive your revenue, but they also carry the highest per-unit cost. If you buy 6 months of supply for an expensive A item, you are tying up a significant amount of working capital in a single SKU. The smarter approach is to order A items more frequently in smaller batches. This keeps inventory turning over quickly, allows you to react promptly when demand deviates from your forecast, and keeps your cash available for other uses.

C items are the inverse. Their per-unit cost is low and their sales volume is minimal. The holding cost of carrying 6 months of a $3 keychain is negligible. Buying C items in bulk means fewer purchase orders, less administrative overhead, and more of your attention freed up for the SKUs that actually move the needle.

The practical framework:

• A items: Review weekly. Order frequently in smaller batches (e.g., 4 to 6 weeks of supply). High turnover, high attention.
• B items: Review bi-weekly or monthly. Order in moderate batches (e.g., 8 to 10 weeks of supply).
• C items: Review monthly or quarterly. Order infrequently in larger batches (e.g., 24 weeks of supply or more). Low turnover, low attention.

This is the cash-flow-aware version of ABC. The service level targets protect you from stockouts. The ordering strategy protects your working capital.

A worked example

Here is a simplified catalog of 10 SKUs for a leather goods store, sorted by 90-day revenue. The unit cost column is what makes the ordering strategy clear:

Just two SKUs generate 75% of the revenue. They are the A items. If the store stocks out of the Brown Tote, it is a crisis. If they stock out of the Gift Box, it is an inconvenience.

Now look at the unit costs. The tote is thirty times more expensive than the gift box. If the store owner carries 6 months of supply for the tote, they tie up tens of thousands of dollars in a single SKU. If they carry 6 months of gift boxes, they tie up a few hundred dollars.

By ordering the A items frequently in small batches, the owner keeps their cash fluid and their turns high. By ordering the C items in bulk once or twice a year, they eliminate the administrative overhead of constantly reordering cheap accessories. The service level targets are set by category. The ordering strategy is set by unit cost and cash flow.

The trap of the complete collection

The hardest part of ABC analysis is emotional. Store owners fall in love with their products. They want to offer a complete collection. They feel guilty when a customer asks for a C item that is out of stock.

You have to separate the emotion from the math. Every dollar tied up in a C item is a dollar you cannot use to buy more A items, run ads, or pay yourself.

If a C item consistently stocks out and customers complain, that is actually a good signal: demand may be increasing. If the data shows it moving up the revenue ranks, reclassify it as a B item and increase its service level. Let the data drive the decision, not the fear of a single missed sale.

A note on SkuClerk and service levels

In the current version of the SkuClerk spreadsheet, the service level is a global setting applied across your entire catalog. It does not calculate ABC categories automatically, and it does not support assigning different service level targets per SKU.

This is a deliberate design choice to keep the initial setup simple. For now, the right approach is to use ABC analysis as the mental model that guides how you allocate your time and your cash, and use SkuClerk's global service level as a reasonable baseline for your catalog as a whole. Operators who want to differentiate by category can manually adjust the safety stock inputs for individual SKUs in the spreadsheet to reflect their ABC-driven targets.

Per-SKU service level configuration, along with a full Plan For Every Part (PFEP) approach, is on the roadmap for the upcoming Shopify App version of SkuClerk.

Common mistakes

1. Using unit count instead of revenue. A SKU that sells 500 units at $2 each is not an A item. A SKU that sells 10 units at $200 each might be. Always rank by revenue contribution, not volume.
2. Running the analysis once and forgetting it. Product popularity changes. A viral post can turn a C item into an A item within a week. Re-run your ABC categorization every quarter.
3. Applying the same percentages to every business. The 80/15/5 revenue split is a starting point, not a law. Some catalogs are more concentrated, some less. Look at your actual data and adjust the thresholds to match your business reality.
4. Ignoring the C items entirely. Low priority is not zero priority. C items still need a reorder point. They just get a lower service level and a less frequent review cycle.
5. Forgetting to update safety stock after reclassification. If a SKU moves from C to A, its Z-score should change from 1.04 to 1.96. The safety stock formula is the same; only the input changes. Make sure your planning model reflects the new category.

How to implement this today

1. Run the numbers. Export your last 90 days of sales and categorize your SKUs into A, B, and C.
2. Add unit costs. Include the wholesale cost per unit so you can see the cash impact of each category's ordering strategy.
3. Update your planning tool. Add an ABC Category column and an Order Strategy column to your spreadsheet.
4. Change your weekly routine. Focus your Monday morning review on A items. Let B and C items run on a longer cycle.

ABC analysis is the connective tissue between all the formulas in this series. Safety stock, reorder points, and EOQ give you the right numbers per SKU. ABC analysis tells you which SKUs deserve the most precise numbers, the most capital protection, and the most frequent attention. Together, they give you a complete planning model that is proportionate to the actual risk and value in your catalog.