Hey everyone — I’ve been poking at inventory workflows for apparel sellers on Shopify as a side project, and I keep hearing that a lot of people still track size x color stock in spreadsheets (especially now that Stocky is gone). Curious how folks here actually handle it day to day:
Do you track stock per size/color combo, or just per product overall?
When you restock a style, how do you decide how many of each size to order? Gut feeling, past sales ratio, something else?
Anything about splitting inventory across locations that’s been painful?
Not selling anything, just trying to understand real workflows before I build more. Would love to hear how you do it (or vent about it)
There are actually several apps that allow tracking not only Size and Color (we own an apparel store and I have a long Nike background), but also any other attribute like “Material” or “Fit” or in shoes, “Width”. One of those apps is our own, which was originally built for clothing stores, but we have expanded to other store types as well (Hobbies, Comics, Gift Shops, Shoe companies, etc.) and therefore support any option possible. Further, we allow custom option values and standardize on those values so you don’t end up with several “shades” of blue just because the supplier or brand got creative with their color naming. If you want, check it out - on the app store at FyreTrail or even just checkout the website at www.fyretrail.com
Feel free to create something, but if you spend some time on the forums looking into this I think you’ll find that there is an absolute large amount of existing applications that do many of the things (generally more) that Stocky did (it’s saturated, but not in a good way). As an app developer and a store owner, I would say there are ample options to choose from already and adding one more to the pile just makes that needle harder to find in the haystack.
We track every size/color combo as its own variant SKU. Product-level totals hide the real problem, like having 20 units left but all in XS.
For reorders, I export the last 8 to 12 weeks by variant and calculate each size’s share of sales. I exclude weeks when a variant was out of stock, otherwise demand gets understated.
For a new style, I use the size curve from the closest similar product, then buy shallow on the first order. After 2 to 4 weeks, I adjust using actual sales.
We target roughly 4 to 6 weeks of cover for core items, less for seasonal pieces.
Across locations, set a small safety stock per variant and use one location as the main fulfillment location. Weekly cycle counts on fast movers catch most issues before they become oversells.
Spreadsheets are useful for reorder planning, but Shopify variant inventory stays the source of truth.
Thanks for the pointer — checked out FyreTrail. Looks like it’s more focused on wholesale PO import and open-to-buy planning, which is a bit different from what I’m poking at, but appreciate the perspective on the space being crowded. Good to keep in mind.
That’s actually very helpful insight on your first impressions reading about FyreTrail - thank you!
FyreTrail is actually centered on Purchasing and tracking Inventory, but with that comes knowing your Open To Buy, Forecasting and Restocking (Reordering). To do that, you need to know WHAT needs ordering (variants) and that’s where the need to track product variants by options like Size and Color (or whatever) come in. Now, that’s not a reach to get there, that’s just illustrating how FyreTrail helps stores with that full-cycle inventory tracking.
This is incredibly helpful, thank you for the detailed breakdown!
The stockout exclusion point especially — I hadn’t accounted for that, and it makes total sense (demand looks lower than it actually is if you don’t factor in the item being unavailable). Going to fix that.
Good to hear the size curve approach for new styles lines up with how you actually do it. Really appreciate you taking the time.
For apparel, we’ve found that tracking inventory at the size/color variant level is pretty much unavoidable. Looking at total inventory for a style is useful for planning, but it doesn’t help much when the sizes that actually sell out are usually the ones customers want most.
Restocking is where things get interesting. Early on, we relied a lot on instinct and ended up with plenty of leftover XS and XXL while constantly running out of M and L. Over time, we started looking at historical sales ratios by style instead. Surprisingly, the “ideal” size curve can vary quite a bit between products, even within the same brand.
The biggest headaches haven’t come from forecasting though. They’ve come from inventory visibility. Once inventory is spread across a retail location, warehouse, pop-up events, or multiple stores, it becomes much easier for stock numbers to drift out of sync than most people expect.
We’ve had situations where the inventory count itself wasn’t wrong, but it wasn’t updated in the right place quickly enough, which created oversells and a lot of manual cleanup afterward.
That’s one reason I’ve seen more merchants focus on inventory synchronization and visibility since Stocky’s shutdown. Some use spreadsheets, some move to ERP-style systems, and others use tools like Easify Inventory Sync when they need inventory shared across stores. The actual forecasting process is often less painful than figuring out which stock number is the “real” one at any given moment.
Curious how many apparel sellers here are still using spreadsheets for size curves versus pulling replenishment decisions directly from sales data. That seems to be where workflows start to diverge.
This is one of those processes that gets painful once the number of variants grows. A simple workflow can keep the variant quantities centralized, flag low-stock combinations, and notify you before you’re caught with an unavailable size/color. If you’re doing any of this manually right now, I can show you what I’d automate.
The whole size curve rests on something nobody has poked at: whether the variant counts are true.
Apparel drifts faster than most categories for a physical reason. One style hangs in two places, a rail and a stockroom bin, with sizes inches apart on the same bar, so a customer puts an M back on the L peg, and somebody at the till scans the S because it sat nearest while the M is what actually walked out of the shop. Nothing errors. Your XS looks healthy for a month, and any spreadsheet built on top inherits those numbers rather than testing them.
The cheap correction is a partial count. One vendor, or one rail, fifteen minutes before opening. A rail counted every six weeks never drifts far enough to poison a size curve.
