Every time your Square POS processes a sale, it generates a data point. Item sold, quantity, time, location. Over weeks and months, those data points accumulate into something valuable: a detailed record of what your customers want, when they want it, and how fast you're selling through your stock.
Most Square merchants use this data for basic sales reporting. Very few use it for what it's actually best at — making inventory decisions.
What Square gives you for inventory management
Square Inventory is genuinely useful for operational basics. You can track stock levels per item and per location, receive low-stock alerts, manage purchase orders, and adjust quantities manually or through automated stock counts. For a small to mid-size retailer, it covers the fundamentals.
Here's what it tracks:
- Current stock quantities by item and location
- Stock alerts when quantities fall below your set threshold
- Stock adjustments with reason codes (received, sold, damaged, etc.)
- Purchase orders to suppliers
- Item catalog with variations, pricing, and SKU numbers
This is inventory management. It answers "what do I have?" and "what's running low?"
What it doesn't do is inventory analytics — the layer that answers "what should I buy, how much, and when?"
Turning POS transaction data into demand signals
Your Square transaction history is a demand forecast waiting to happen. Every completed sale is a confirmed data point: a specific customer wanted a specific product at a specific time. Aggregate enough of these data points, and patterns emerge.
Sales velocity by item
Sales velocity is the rate at which a product sells over a given period. It's the single most important metric for inventory decisions, and Square doesn't calculate it for you.
The formula is straightforward: units sold divided by the number of days in the period. If you sold 120 units of a product over 30 days, your velocity is 4 units per day. But the useful application isn't just the average — it's the trend.
A product that sold 6 units per day last month and 4 units per day this month has declining velocity. A product that went from 2 to 5 units per day is accelerating. These trends should directly inform your purchase orders. Square's low-stock alert doesn't know the difference between a product that's selling faster than expected and one that's slowing down — it just knows the number hit your threshold.
Sales velocity by location
For multi-location merchants, item-level velocity varies significantly by store. A product moving 8 units per day at your downtown location might crawl at 2 units per day at your suburban store. This isn't just a restocking insight — it's an allocation insight. Your next purchase order should distribute stock proportionally to where it actually sells, not evenly across locations.
Time-based patterns
Look at your POS data over longer periods and you'll see patterns that daily or weekly reports obscure.
Day-of-week patterns. Some products spike on weekends. Others sell steadily throughout the week. Knowing this helps you time deliveries and floor replenishment.
Monthly cycles. Certain categories follow predictable monthly rhythms tied to payroll cycles, event calendars, or local patterns. If your data shows a consistent revenue dip in the second week of each month, that's a staffing and inventory signal.
Seasonal patterns. This is the big one. Square has your transaction history going back months or even a few seasons. That history tells you exactly when seasonal demand starts rising, when it peaks, and when it falls off. Buying seasonal inventory based on last season's POS data is dramatically more accurate than guessing.
Identifying slow movers
Every retail store has products that sit on shelves too long. The cost isn't just the capital tied up in unsold stock — it's the opportunity cost of shelf space that could hold something better, plus potential markdowns when you eventually try to move it.
Square will tell you current stock levels. What it won't tell you is how long that stock has been sitting there relative to its sell-through rate.
A product with 50 units in stock and a velocity of 1 unit per day has about 50 days of supply. That's probably fine. A product with 50 units in stock and a velocity of 0.3 units per day has nearly 6 months of supply — that's a problem.
Days of supply (current stock divided by daily sales velocity) is the metric that identifies slow movers. Calculate this for every SKU, and you'll quickly see which products are sitting on capital you could deploy elsewhere.
Once you've identified slow movers, you have options: mark them down, bundle them with faster sellers, reduce or eliminate reorders, or move excess stock to a location where they sell better.
ABC classification for your Square inventory
ABC analysis is a standard inventory management framework that segments your products into three tiers based on their contribution to revenue.
- A items — The top 10-20% of products that typically generate 70-80% of revenue. These are your stars. Never run out of A items.
- B items — The middle tier, maybe 20-30% of products generating 15-20% of revenue. Important but not critical. Moderate safety stock.
- C items — The long tail. 50-70% of your catalog that generates 5-10% of revenue. Keep minimal stock. These are your markdown and discontinuation candidates.
Square doesn't classify your inventory this way. But the data to do it is all in your POS transaction history. Export your item sales report, sort by revenue contribution, and draw the lines.
The power of ABC classification is in how it changes your behavior. You stop treating all products equally. A items get priority shelf space, aggressive reorder points, and safety stock buffers. C items get reviewed quarterly and culled when they stop earning their space.
Calculating reorder points from POS data
A reorder point is the stock level at which you should place your next purchase order. Set it too high and you're tying up capital in excess inventory. Set it too low and you risk stockouts — missed sales and frustrated customers.
The basic formula:
Reorder Point = (Daily Sales Velocity x Lead Time in Days) + Safety Stock
Lead time is how long it takes from placing an order to receiving it. If your supplier delivers in 7 days and you sell 4 units per day, you need to reorder when you hit 28 units — plus whatever safety stock buffer you want for demand variability.
Safety stock accounts for uncertainty. If your daily velocity fluctuates between 2 and 6 units, you need more buffer than if it's consistently 3.5 to 4.5. The variability of your POS data directly informs how much safety stock each product needs.
Square's stock alerts use a single threshold number you set manually. That's a static guess. Reorder points calculated from actual POS velocity and supplier lead times are dynamic and far more accurate.
For each of your A items, calculate the reorder point. Update it monthly as velocity changes. For B items, review quarterly. For C items, consider whether you need to reorder at all.
What Square Inventory can't tell you
Square's inventory features serve the operational layer well. The analytical gaps are where merchants struggle:
- No sell-through rate calculations. Stock levels without velocity context.
- No days-of-supply metric. No way to see how long current inventory will last at the current sales rate.
- No ABC classification. All products treated equally in the interface.
- No demand trend analysis. Current stock alerts don't account for accelerating or decelerating sales.
- No cross-location velocity comparison. Inventory data is location-scoped without a unified analytical view.
- No seasonal demand overlays. Historical patterns aren't surfaced to inform future purchasing.
These gaps don't mean Square is a poor inventory tool. They mean it's an inventory management tool, not an inventory analytics tool. The distinction matters.
How Spark connects to Square for inventory analytics
Spark by MishiPay connects to Square via OAuth and pulls your full transaction history alongside your current catalog and inventory data. This combination — sales data plus stock data — is what enables real inventory analytics.
With your Square data connected, you can ask questions like:
"Which of my products have the highest days-of-supply and should be marked down?"
"What are my reorder points for A items based on the last 90 days of sales velocity?"
"Which products are accelerating in sales and need larger purchase orders?"
"How should I allocate my next order across locations based on sell-through rates?"
Spark runs these calculations across your full catalog and all locations, surfacing the inventory intelligence that Square's built-in reports don't provide. The analysis updates as new transactions come in, so your reorder decisions are based on current velocity, not last month's export.
For merchants who also sell through Shopify, WooCommerce, or another platform, Spark unifies that data too — giving you a single view of demand across all channels, which is critical for setting accurate reorder points.
Start with velocity
If you take one thing from this article, let it be this: calculate sales velocity for your top 20 products. Units sold per day, trended over the last 90 days. That single metric will change how you buy, how you allocate, and how you manage shelf space.
Square gives you the raw data. The step from data to intelligence is where most merchants stall. Don't let it sit in reports — put it to work.
Turn your Square POS data into inventory intelligence
Spark analyzes your Square transaction history to calculate sell-through rates, reorder points, and demand trends across all locations.