Anyone here running a smaller Shopify store and still using spreadsheets or CSVs for inventory? How do you figure out what to reorder and when? Curious what part of that process is the biggest headache for you.
AI-generated summary
A small Shopify-store owner asked how spreadsheet/CSV users decide what and when to reorder, then shared an unfinished CSV-based reorder recommendation concept for feedback.
The main consensus is that basic stock tracking is less difficult than calculating SKU-level reorder timing and quantity. Suggested approaches include using each product’s sales velocity, supplier lead time, and a safety buffer, rather than one storewide threshold. Several replies warned that rolling averages can fail for slow-moving or irregular SKUs.
Key complications raised:
- Sold-out days can make demand look lower than it really is.
- Confirmed incoming stock and committed units should be considered to avoid duplicate orders.
- Buffers should vary by volatility, not be flat across all products.
- Slow movers may need min/max or periodic review instead of continuous triggers.
- Cash availability after a recommended purchase order remains a separate unresolved decision.
Several app developers disclosed relevant tools for reorder planning, forecasting, or CSV cleanup. The discussion remains open, with no single solution chosen, but strong feedback that any CSV workflow should explain its calculations and flag missing or unreliable data.
Hey @hennyhana
Yeah, I’ve dealt with this before and honestly, the annoying part isn’t really tracking the stock, it’s knowing when you should actually reorder. I usually look at what’s been selling recently, how much stock is left and how long the supplier normally takes to deliver, but once you have a lot of products it gets pretty messy doing all of that manually in a spreadsheet. The worst thing is either ordering too early and having money sitting in stock, or waiting too long and suddenly realizing your best seller is almost out of stock. That’s probably the part I’d want to make as automatic as possible.
If there’s anything you need help with on your Shopify store, feel free to reach out or share the details here. I’ll be happy to take a look and help you figure out the best way forward.
Best Regards,
Sam creativity
Thanks, that’s really helpful. Makes sense that the reorder timing gets way more complicated once there are a lot of products involved. Appreciate the insight!
I created a quick concept test for the reorder problem. It’s unfinished, but I’m curious — would this kind of workflow actually help people managing inventory with spreadsheets?
The headache that doesn’t go away with more spreadsheet columns is turning “running low” into “how much”. Days-of-stock from recent sales works fine until the catalog is big enough that some SKUs sell twice a week and others twice a quarter — a 30-day average is either noise or a random zero on the slow ones, and one reorder point for the whole store fires too late on the fast movers and too often on the slow ones.
Two things that keep the CSV approach working past a handful of products: keep each SKU’s own supplier lead time next to it, so the reorder point is that lead time’s worth of sales plus a buffer rather than a guess; and for anything with long gaps between sales, track typical sale size and typical gap instead of a rolling average, which is what actually breaks first as the sheet grows.
Disclosure: I’m the developer of Tallyfold Restock Planner. It builds an order-by date and quantity per variant from your sales history this way and explains each number, with a CSV export. Read-only — no POS or storefront changes. $39–149/month depending on your Shopify plan, 30-day free trial.
The headache almost always comes from not having a real reorder point per SKU. Most people skip it. A rough number still works: average units sold per week times your supplier’s lead time in weeks, plus a small buffer for the slower movers. Compare that to current stock and you know when to order. Not a gut feeling on Monday.
You do not need to buy anything to start. Shopify’s own inventory reports already show current stock and sell-through by product, so the formula above can live in a spreadsheet from day one. Want a nudge instead? Flow can notify you when a variant drops below a set quantity, though it still will not calculate the reorder point itself, you feed it that number.
I build Binly, so take that into account. Reorder points built from your own supplier lead times instead of a guess is exactly what we compute.
Good thread — this is the exact wall most spreadsheet-based shops hit once SKU count grows.
The “avg weekly sales × lead time + buffer” formula is a solid base, but the buffer is where people usually get burned — a flat buffer across all SKUs either overstocks the stable sellers or leaves the volatile ones exposed. Two SKUs both averaging 10/week can need very different safety stock depending on how erratic that 10 actually is. Same with lead times — using the supplier’s average quote instead of their worst realistic case means you stock out whenever they have a slow month.
Slow movers are their own problem too. Rolling averages get misleading at low volume (1/week for 8 weeks looks identical to 8 units once and nothing since), so min/max or periodic review tends to work better than a continuous trigger there.
And Flow’s fine as a notification layer, but you’re still manually setting and maintaining the threshold per SKU — it doesn’t solve the actual math, just alerts on it.
I’m on the onboarding/support team at SKUSavvy, so I spend a lot of my time walking merchants through exactly this problem. We built SKU-level reorder points that pull from actual velocity + lead-time data instead of one storewide number — partly because we kept seeing customers hit this same wall. Happy to answer specifics if useful.
Hi hennyhana! One thing I’d add to the reorder-point advice is that knowing when stock is running low doesn’t always tell you how much you can comfortably afford to reorder.
For a small store using spreadsheets, do you find the harder part is forecasting demand and choosing quantities, or checking whether a larger reorder would leave enough cash for ads, shipping, and other upcoming expenses?
I’m interested in how merchants handle that trade-off before placing an order.
For the CSV concept test, I’d add two checks before recommending a purchase: stockout days and already-confirmed inbound units. If a SKU sold 20 units over 30 days but was unavailable for 20 of them, dividing by 30 understates observed demand while it was available. Flag that case rather than treating the average as a reliable forecast.
Also distinguish usable on-hand stock, committed units and confirmed incoming stock. Otherwise a low-stock recommendation can create a duplicate supplier order. A small explanation beside each recommendation—data window, availability gaps, inbound quantity and missing inputs—would make the test more useful than a single unexplained reorder number.
Disclosure: I’m developing StoreOpps. Do your current exports include availability history and open purchase orders, or just today’s stock and past sales?
@hennyhana the headache I kept hitting in the spreadsheet version was the days a product was sold out: they count as days nobody wanted it, so the best sellers look slow and get under-ordered again. Full disclosure: I build Restock Forecast, so I am biased.
For a smaller store it is free for up to 50 products, with no time limit. For each product it shows the date it runs out and how many to order, worked out from your own sales with the sold-out days taken out, and it emails you only when something actually needs ordering.
If you later want purchase orders and receiving as well, you can use every feature free for 30 days, then it is $19.99/month.
Your CSV reorder concept is a concrete use case for a small file-only pilot. I can take one inventory CSV/XLSX of up to 500 rows and 15 columns and return a cleaned reorder-review sheet, with SKU/product/stock fields normalized where present, missing or ambiguous data flagged, and a brief change report based only on the supplied data.
Price: US$19. No store access or credentials needed; this does not include Shopify import, an automated connection, or a guaranteed forecast or purchasing recommendation. If you have a current export, reply with its format and approximate size. We would confirm the exact scope, deliverable, price, and payment method before any work.
One part of reordering I’m curious about is what happens after you know what needs to be reordered.
Say the reorder calculation suggests placing a €4–5k PO. How do you decide whether the business can actually afford to commit that amount right now?
Do you factor in upcoming payments, a minimum cash buffer or a slower-sales scenario before placing the PO, or is that usually a separate decision?
Great thread. Most of the replies here are formulas, and they work, but they all share one weakness: they treat every SKU the same way. One average, one buffer, one lead time.
What changed things for me was the other way around: learning how your shop actually sells, per SKU. Which products sell steadily and which come in spikes, which ones sell out before you notice, how each one behaves in each season and each location. Once you have that for every SKU, you’re not reading reports anymore, you’re getting a decision: what to reorder, how much, and when, with the reason behind it.
In a spreadsheet you can get part of the way: track each SKU separately, mark the days it was out of stock, and look at its own pattern instead of a store-wide rule.
But I think we are in the pace that you done with reports and you can move to solutions
Full disclosure: I’m the founder of Sizo. It trains a model on your Shopify store’s data and turns it into these per-SKU decisions (there’s a free plan). But even without a tool, moving from “what sold last month” to “how does this SKU really behave” is the step that makes the biggest difference.