12 Shopify Inventory KPIs to Track, With Formulas and Worked Examples
Inventory KPIs turn stock levels and sales into numbers you can compare from month to month. This guide defines 12 of them, shows each formula with a worked example, and explains how to read the result and what to do about it.
How to use inventory KPIs
A KPI is only useful if you calculate it the same way each time and compare it with something meaningful. Three habits make that work:
- Compare with your own history first. Your category, margins, lead times and supplier terms differ from every other store's, so a figure borrowed from someone else's store tells you little. Watch your trend instead.
- Work at SKU or category level. A store-wide average can look fine while a large group of SKUs is a problem.
- Compare against the same period last year. Stock builds ahead of a peak season and falls after it. Rising inventory in the weeks before peak is planning. The same pattern in a quiet month deserves a closer look. See seasonal inventory planning.
Your data comes from your order history (units sold, revenue) and your inventory records (units on hand), plus unit cost from your product or accounting records. Use cost values for inventory unless a formula says otherwise.
The 12 KPIs
1. Inventory turnover
Use COGS and inventory at cost, for the same period. Average inventory is (beginning value + ending value) ÷ 2, or the average of monthly values if your stock swings with the seasons.
Hypothetical example. Annual COGS is $240,000 and average inventory at cost is $60,000. Turnover = 240,000 ÷ 60,000 = 4.0 turns a year.
Higher means stock converts to sales faster. Very high can mean thin stock and missed sales. See the inventory turnover ratio guide.
2. Days of inventory
It is turnover expressed in days. With the figures above, DSI = 60,000 ÷ 240,000 × 365 = 91.25 days, which is the same as 365 ÷ 4.0. If you use quarterly COGS, use roughly 90 days instead of 365.
For individual SKUs, use a forward-looking version:
Hypothetical example. You hold 140 units and sell 10 a day, so days of supply = 14. Supplier lead time is 21 days. Ordering today would leave you out of stock for about 21 − 14 = 7 days, assuming steady sales.
3. Sell-through rate
Measure it over a fixed window, such as the first 30, 60 or 90 days after receiving stock. If you received 400 units and sold 300 in 60 days, sell-through is 75%. A low early figure is a signal to hold back on reorders or promote. A very high figure can mean you ran out early and lost sales.
4. Inventory-to-sales ratio
Use the same valuation basis for both, either both at cost or both at retail. If inventory is $90,000 at retail and monthly sales are $45,000 at retail, the ratio is 2.0, or about two months of sales on hand. The trend matters most. A ratio that rises month after month means you are accumulating stock faster than you sell it.
5. Stockout rate
The time-based version is steadier than a one-day snapshot.
Hypothetical example. You have 200 active SKUs and 8 are out of stock today, so the point-in-time rate is 8 ÷ 200 × 100 = 4%. Over a 30-day month, 300 SKU-days out of stock across those 200 SKUs gives 300 ÷ (200 × 30) × 100 = 5%.
For lost sales, say one SKU is out of stock for 6 days, normally sells 10 units a day and is priced at $25. Estimated lost sales = 6 × 10 × $25 = $1,500.
Treat the lost-sales figure as a rough estimate, because some customers wait or buy something else, and demand during the stockout may have been higher or lower than average.
Weight stockouts by revenue. A stockout on a top seller and one on a slow accessory are very different problems. See preventing stockouts.
6. Backorder rate
Hypothetical example. Customers order 200 units of a SKU in a month and 8 of those units are backordered. Backorder rate = 8 ÷ 200 × 100 = 4%.
Accepting a backorder can keep a sale you would otherwise lose, but a persistently high rate signals a gap between demand and supply. Track the average time to fulfill a backorder alongside it. See backorder management.
7. Safety stock level
Here z is the service-level factor (about 1.65 for a 95% chance of not stocking out during a cycle), LT is average lead time in days, σd is the standard deviation of daily demand in units, d̄ is average daily demand in units and σLT is the standard deviation of lead time in days. If lead time is fixed, the formula reduces to z × σd × √LT.
Hypothetical example. z = 1.65, LT = 14 days, d̄ = 10 units a day, σd = 3 units a day, σLT = 2 days. Inside the root: 14 × 3² = 126 and 10² × 2² = 400, so the sum is 526. The square root of 526 is about 22.9, and 1.65 × 22.9 ≈ 37.8, so hold about 38 units.
As a KPI, compare the safety stock you hold with what the formula says. See safety stock formula.
8. On-time replenishment rate
Hypothetical example. You place 20 reorders in a quarter and 17 arrive before the stock runs out. On-time replenishment rate = 17 ÷ 20 × 100 = 85%.
This shows how well your reorder points work. When a reorder misses, log the reason: supplier delay, demand spike or wrong lead-time assumption. You can also measure each supplier on the share of purchase orders received on time with the right items and quantities. See reorder point formula.
9. Carrying cost percentage
Carrying costs include storage, insurance, cost of capital, handling, shrinkage and loss in value. If those total $12,000 a year on $60,000 of average inventory, carrying cost is 12,000 ÷ 60,000 × 100 = 20%. See inventory carrying cost formula.
10. GMROI
Gross margin return on investment shows how many dollars of gross margin each dollar of inventory earns. It combines margin and speed in one number.
Hypothetical example. Two products each sell $100,000 a year. Product A has a 60% gross margin and turns once a year. COGS is $40,000, gross margin is $60,000 and average inventory is $40,000, so GMROI = 60,000 ÷ 40,000 = 1.5. Product B has a 20% margin and turns 12 times a year. COGS is $80,000, gross margin is $20,000 and average inventory is 80,000 ÷ 12 ≈ $6,667, so GMROI = 20,000 ÷ 6,667 = 3.0.
The low-margin, fast-turning product earns more per inventory dollar. GMROI counts only gross margin, so compare it with your carrying cost expressed as a decimal (20% = 0.20) and with your other costs.
11. Dead stock percentage
Hypothetical example. Say $9,000 of your $60,000 inventory at cost has had no sales in your window. Dead stock = 9,000 ÷ 60,000 × 100 = 15%.
Define "dead" with a no-sales window that suits your products, then track the percentage monthly. See dead stock management for how to find and clear it.
12. Order accuracy rate
Hypothetical example. You ship 500 orders in a month and 485 go out correct. Order accuracy = 485 ÷ 500 × 100 = 97%.
Inventory errors become fulfillment errors: wrong variant, wrong quantity, items that were not actually in stock. Common causes are weak counting, manual entry mistakes, picking errors and records that do not match the shelf. See inventory shrinkage.
A review rhythm
You do not need all 12 every day. Start with five: turnover, sell-through, days of supply, stockout rate and GMROI. Add others as your catalog or supply chain grows.
- Daily: which SKUs are out of stock, and any fulfillment errors.
- Weekly: sell-through on recent arrivals, days of supply against lead time, and backorders.
- Monthly: turnover, days of inventory, inventory-to-sales ratio, GMROI, carrying cost, dead stock, safety stock and on-time replenishment.
Calculating by hand is fine if you do it on a schedule. Consistent definitions matter more than precision.
Mistakes to avoid
- Relying on averages. If half your inventory value turns 10 times a year and the other half turns once, the blended store-wide figure is 5.5, and it hides a serious problem. Drill down, using ABC analysis to prioritize.
- Ignoring seasonality. A product that sold 50 units in February and 100 in March may not be growing. March may be its peak. Compare against the same month last year.
- Optimizing one KPI alone. Cutting stock lifts turnover and lowers carrying cost, but it can raise stockout rate and cost sales. The KPIs work as a set.
- Tracking too many at once. A metric you review and act on beats twenty you glance at.
- Changing definitions. If you switch the window or valuation basis, the trend breaks. Write each definition down.
From KPI to action
| Signal | Likely response |
|---|---|
| Turnover falling, days of inventory rising | Find the slow SKUs, promote or bundle them, cut the next reorder quantities |
| Stockout rate above your target | Check lead times and safety stock on the affected SKUs |
| GMROI low on a category | Review pricing, supplier cost and stock levels, or consider dropping it |
| Dead stock percentage rising | Clear it with bundles, markdowns or donation, and review how it was bought |
| Carrying cost rising | Review storage fees, average stock and supplier terms |
| Backorders increasing | Review forecasts, reorder points and backup suppliers |
Key takeaways
- Define each KPI precisely, with the period and valuation basis, and keep it fixed.
- Compare with your own history and the same period last year, not with other stores.
- Work at SKU or category level, and weight stockouts by revenue.
- GMROI combines margin and speed, so use it to compare products.
- Start with a few KPIs, review them on a schedule and tie each to an action.