The most expensive mistake in plus size buying is spreading the budget evenly across every size. An even buy guarantees that your best-selling sizes run out while your slowest sizes sit on the rack, and it happens in the first month. The fix is not a published size curve copied from somewhere else; it is a measurement habit that produces your own curve within a season or two.
I am Carina Hatton, boutique owner since 2013 and ecommerce coach since 2019. There is no universal plus size distribution that applies to every store, and anyone quoting one is describing their customers, not yours. Everything below is method plus clearly labelled hypothetical examples.
Quick answer
Planning a first collection or new drop? Use the Boutique Inventory Planner to estimate revenue, profit, and overbuying risk before you order.
Open the Boutique Inventory Planner →What a size curve is and why yours is unique
A size curve is the distribution of units you buy across your size range. If you carry six sizes and buy twelve units of a style, the curve decides whether that is two of each or a weighted spread.
Your curve depends on:
- The customers your marketing actually reaches
- Your location, if you have a storefront
- Your price point and category mix
- The specific vendor's sizing, since a 2X is not the same garment everywhere
- The style itself, because a fitted dress and an oversized cardigan sell different distributions
Two plus size boutiques in the same town, at the same price point, can sell genuinely different curves because they attract different customers. That is why this article gives you the method rather than a table to copy.
Building your curve from real sales
Size share = units sold in that size ÷ total units sold
Sell-through by size = units sold in that size ÷ units received in that size
Units for next buy = planned style depth × adjusted size share
A hypothetical store after one season, having sold 400 units across a six-size range:
| Size | Received | Sold | Sell-through | Size share | Read |
|---|---|---|---|---|---|
| 1X | 95 | 72 | 76% | 18% | Healthy |
| 2X | 110 | 104 | 95% | 26% | Underbought |
| 3X | 105 | 100 | 95% | 25% | Underbought |
| 4X | 80 | 68 | 85% | 17% | About right |
| 5X | 60 | 38 | 63% | 9.5% | Slightly overbought |
| 6X | 50 | 18 | 36% | 4.5% | Overbought |
This is one hypothetical store's data. Notice what share of sales alone would have told you: that 2X and 3X are just over half the business. Notice what sell-through adds: both sizes hit 95%, meaning demand was cut off by supply, so their true share is higher than 26% and 25%.
Adjusting share for constrained demand
Any size above roughly 90% sell-through was supply-limited. Weight it upward on the next buy rather than taking its measured share at face value. Any size below about 50% sell-through was overbought, and its share should come down. Applying that judgement to the table above, the next buy might shift several points from 5X and 6X into 2X and 3X, while keeping 6X represented rather than dropping it, because the customers who wear it are the least served elsewhere and the most loyal when served.
The argument against quietly cutting a size
The data above tempts you to drop 6X. Think carefully before doing it.
- The customer who wears your largest size has the fewest alternatives and the strongest loyalty when a store carries her
- A size that is stocked inconsistently sells badly partly because customers stop checking
- Dropping a size quietly is noticed and damages trust in the store's promise
The reasonable middle path is to keep the size in the range while buying it shallower, concentrating it in the styles and categories where it performs best, and stating your range honestly. Cutting depth is a buying decision; cutting the size is a positioning decision.
Tops and bottoms need different curves
This is specific to this niche and frequently missed. Many customers wear a different size on top than on the bottom, so applying one curve across all categories creates predictable stockouts and predictable leftovers.
| Category | Fit risk | Depth approach |
|---|---|---|
| Tops and blouses | Lower, styles are often forgiving | Deeper depth, wider size spread, fastest to reorder |
| Dresses | Moderate to high, fitted styles are unforgiving | Moderate depth, concentrate in your strongest sizes |
| Bottoms | Highest, hip and waist ratios vary widely | Shallow until a vendor is proven, then deepen aggressively |
| Layers and outerwear | Low, worn open and over other pieces | Fewer sizes can work, good candidate for wide spread |
| Accessories | None | No size decision, pure margin and basket builder |
Track size share separately for tops and bottoms. It is entirely normal for them to differ, and the difference is worth real money once you buy to it.
Prepacks and what they cost you
Many vendors sell prepacks: a fixed bundle of sizes per style. They are convenient and they encode the vendor's assumption about an average store.
- Use prepacks when you are new to a vendor, testing a style, or have no data yet
- Move to open stock once you know your curve, even at a slightly higher per-unit cost
- Calculate the trade-off honestly: paying a little more per unit for the right sizes is usually cheaper than marking down the wrong ones
A hypothetical: a prepack of twelve includes two units of a size that consistently sells through at 36% for you. Across ten styles that is twenty units you will likely discount. If the discount averages 40% off a $48 retail, that is roughly $384 of margin given away, which will usually exceed the premium for buying open stock. Ask every vendor whether open stock is available and at what minimum. The mechanics of minimums are in minimum order quantity.
Letter sizing, numeric sizing and extended ranges
Vendors disagree about how to label sizes, and your customers do not care whose system it is. Your job is to translate consistently.
- Maintain your own master measurement chart and map every vendor's sizes onto it
- Publish the garment measurements, not just the label, because measurements are the only thing that transfers across vendors
- Note where a vendor's label disagrees with your chart and say so on the product page
- Never assume a 2X from one vendor equals a 2X from another, and never assume a numeric size maps cleanly onto a letter size
This translation work is the single most valuable operational habit in a plus size boutique. It reduces returns, builds trust and makes your size data comparable across vendors, which is what makes the curve calculation meaningful in the first place.
Basics and fashion need different depth
| Basics | Fashion | |
|---|---|---|
| Depth | Deep, across the full size range | Shallow, concentrated in top-performing sizes |
| Reorder | Reorder continuously while it sells | Reorder only inside the trend window |
| Markdown plan | Rarely needed | Planned from the buy |
| Photography | Worth investing in, reused for seasons | Fast and current |
A store that is mostly fashion has to re-earn its assortment every season. A store with a strong basics core has a reorderable spine and only has to gamble on the layer above it. The per-style unit question in general is covered in how many units per style should a boutique buy.
A hypothetical opening buy
Illustration only, for a $7,000 opening inventory budget with no prior sales data:
| Decision | Approach for a first buy |
|---|---|
| Style count | Modest, so each style can carry a real size spread |
| Size spread | Weighted toward the middle of your range, with every size represented |
| Category split | Tops-led, cautious on bottoms until vendors are proven |
| Basics versus fashion | Majority basics, a small fashion layer to read taste |
| Reorder reserve | Hold back roughly 15% to restock the first sell-outs |
| Vendor count | Few enough to learn each one's fit properly |
That last row matters more here than in most categories. Buying from eight vendors on a first order means eight different sizing systems, none of which you understand yet, and returns you cannot attribute. Three or four vendors gives you clean data. The general first-order framework is in how to split your first wholesale order.
Tracking size performance
- Create a variant per size so every sale records the size, not just the style
- Report weekly on units sold by size, overall and within each category
- Log every sell-out and the date, because that is your constrained-demand signal
- Record returns by size and reason, since a size with high "too small" returns means a vendor grading problem rather than a demand problem
- Review the whole picture before every buying appointment
Method is in sell-through rate for boutiques and inventory management.
Reorder rules and stockouts
A hypothetical rule set to adapt:
| Signal | Action |
|---|---|
| One size sold out, others still available | Reorder that size only, and weight it higher next season |
| Whole style sold through quickly | Reorder the full run and treat the style as core |
| Slow in every size | Style problem, not a sizing problem. Mark down, do not reorder |
| Only the extremes remain | Cross-merchandise, promote to a size-specific list, then mark down |
| High "too small" returns in one size | Vendor grading issue. Fix the fit note, reconsider the vendor |
Control the total with open to buy so reorders never quietly overrun the season's budget, and check discount decisions in the Markdown Calculator.
Dealing with excess in a specific size
Leftover units in one size are cash sitting still. Options in order:
- Email customers who have previously bought that size, since you already know who they are
- Bundle with a well-performing item rather than discounting alone
- Stage the markdown rather than making one large cut
- Clear it and buy the lesson, because the floor space and the cash are worth more than the last few dollars
The ongoing cost of not doing this is quantified in inventory carrying cost.
Building the buying worksheet
Everything above becomes practical when it sits on one sheet you fill in before each buying appointment. Here is the structure, with hypothetical numbers to show how it flows.
| Step | Input | Hypothetical |
|---|---|---|
| 1. Season budget | Open to buy at cost for the period | $6,000 |
| 2. Reserve | Held back for reorders | $900 (15%) |
| 3. Spendable now | Budget minus reserve | $5,100 |
| 4. Category split | Tops, dresses, bottoms, layers, accessories | $1,785 / $1,020 / $1,020 / $765 / $510 |
| 5. Style count | Category dollars / (landed cost x planned depth) | Set per category |
| 6. Size split | Your measured curve, adjusted for constrained sizes | Applied per style |
| 7. Check | Total committed against step 3 | Must not exceed |
Styles affordable in a category = category budget / (average landed cost x units per style)
Units for a size = units per style x that size's adjusted share
Working step 5 for tops: with $1,785, an average landed cost of $14 and planned depth of 12 units per style, that is $168 per style and about ten styles. Step 6 then splits each style's twelve units across your size range using your adjusted curve rather than two of each.
The reason to do this before the appointment rather than at it is simple. In the room, with a rep and a deadline, style count and depth get decided emotionally and the size split gets decided by whatever prepack is offered. With the sheet in front of you, the only open question is which styles, which is the decision you are actually good at.
Reviewing the sheet afterwards
Keep the worksheet and write the results on it at the end of the season. Three columns turn it from a buying tool into a learning tool:
- Planned versus received. Vendors substitute and cancel. If a third of what you planned never arrived, that explains a weak season better than any demand theory.
- Sold by size against the curve you used. This is how the curve improves, and it only works if the curve you actually bought to is written down.
- Markdown taken by category. Shows which category was overbought, which is usually clearer in hindsight than in the room.
After two seasons of this you stop guessing. You will know that a particular vendor's bottoms run small and need a shifted curve, that your top sizes sell through fastest in basics and slowest in prints, and roughly how much reserve you actually use. None of that is available from a published benchmark, and all of it is available from your own sheet.
Keep the totals honest with open to buy, check the cost of what does not move in inventory carrying cost, and sanity-check pricing in the Profit Margin Calculator.
Related: how to start a plus size boutique and plus size wholesale vendors.