Sell-through rate tells you what share of the units you brought in have actually sold within a chosen window, and in premium drinkware it is only meaningful when you read it alongside weeks of supply, GMROI and attach rate — and against your own baseline rather than someone else's. The trap in a high-ticket, slow-turn category is borrowing a benchmark. A number that describes a fast-moving accessory shelf makes a healthy titanium display look broken, and you end up dropping lines that were performing exactly as they should. This article teaches the four calculations, how to read each one, and how to set your own baseline. Deliberately, it contains no industry benchmark figures — a benchmark you did not measure yourself is a guess wearing a suit.
- Four numbers cover it: sell-through tells you movement, weeks of supply tells you timing, GMROI tells you whether the money worked, and attach rate tells you whether the category is pulling its weight.
- A ratio without a window is meaningless: the same SKU can show a strong or weak sell-through purely by whether you measured four weeks or a quarter.
- Your baseline is yours: in a slow-turn premium category, the only useful comparison is this SKU against your own trailing history and against the other SKUs on the same fixture.
- Returns distort everything: net your figures of returns before you read them — and note that a coating-free vessel with a limited lifetime warranty gives you fewer of them to net out.
- Terms are scoped, not published: order quantities and trade terms are discussed case-by-case through TAIC's Wholesale & Trade channel, so your inputs can be tuned once you know your numbers.
The four numbers worth tracking
Fix the definitions first, because most disagreements about performance turn out to be disagreements about arithmetic. Each metric below answers a different question and misleads in a predictable way when read alone. Letters are placeholders for your own figures.
| Metric | Formula | Question it answers | How it misleads alone |
|---|---|---|---|
| Sell-through rate | Units sold (S) ÷ units received (R), over a stated window | Did the buy move? | Rewards under-buying — a tiny order sells through fully and still starves the shelf |
| Weeks of supply | Units on hand (H) ÷ average weekly units sold (W) | How long before I run out? | Unstable when W is small; one lumpy week swings it wildly |
| GMROI | Gross margin currency (G) ÷ average inventory at cost (C) | Did the money invested work? | Ignores whether the stock was there when customers asked for it |
| Attach rate | Transactions containing the category (A) ÷ total transactions (T) | Is this category pulling the basket? | Says nothing about which SKU did the pulling |
Takeaway: read the four together — movement, timing, money, and basket pull — because each one alone points you toward a different wrong decision.
Sell-through: the calculation and the window
Sell-through is units sold divided by units received, expressed as a percentage, across a window you state explicitly. The window is not a detail — it is half the metric. Measure a premium titanium tumbler over four weeks and you will see a small number; measure the same unit over a full quarter and the picture changes entirely, without a single thing having changed on the shelf.
For a slow-turn premium category, pick a window long enough to contain a realistic decision cycle, use the same window every time, and label it in every report. Two more rules keep the number honest. Decide whether you are measuring against the original receipt or against cumulative receipts including reorders, and never mix the two. And net out returns, because a unit that sold and came back is not a sale. Then compare like with like: this quarter against last quarter, this SKU against its shelf-mates.
Takeaway: state the window, fix the receipt basis, net the returns — then only compare sell-through against your own history.
Weeks of supply: the number that triggers your reorder
Sell-through is the rear-view mirror; weeks of supply is the windscreen. Divide units on hand by average weekly units sold and you get the weeks before the shelf empties at the current rate — the figure a replenishment decision actually hangs on, and why it belongs in your reorder trigger rather than sell-through.
Two adjustments make it reliable here. Calculate the weekly average across a long trailing window so lumpy weeks cancel out, and exclude display units from "on hand" — a vessel on a plinth is merchandising, not stock, and counting it quietly under-orders your most visible line. When cover falls below the time it takes to get a replacement onto the floor, you are already late; that is the real trigger, and why a reorder point belongs in time rather than units. Our piece on building a balanced titanium drinkware assortment covers the shelf those figures describe.
Takeaway: express your reorder point in weeks of cover, not in a unit threshold, and exclude display pieces from on-hand stock.
GMROI and attach rate: reading money, not movement
A SKU can move well and still be a poor use of your capital, which is what GMROI exists to catch. Divide the gross margin currency a line generated by the average inventory at cost you tied up to generate it. Above one means the line returned more gross margin than the average cost sitting in it; below one means it did not. That is a directional read on capital efficiency, and far more useful in a premium category than unit counts, because premium lines earn their place per unit rather than per transaction.
Attach rate then tells you whether the category is doing work beyond its own line. If titanium drinkware appears in a rising share of your transactions, it is pulling baskets and justifying its floor space before you even look at its margin. The table below is illustrative arithmetic only — the figures are invented to demonstrate the calculation and are not benchmarks, targets, or claims about what any store should expect.
| Metric | Illustrative inputs (invented) | Calculation | Illustrative result |
|---|---|---|---|
| Sell-through | Received R = 10, sold S = 4 in one quarter | 4 ÷ 10 | 40% for that stated quarter |
| Weeks of supply | On hand H = 9, weekly average W = 0.5 | 9 ÷ 0.5 | 18 weeks of cover |
| GMROI | Gross margin G = 900, average inventory at cost C = 600 | 900 ÷ 600 | 1.5 |
| Attach rate | Transactions with category A = 6, total transactions T = 30 | 6 ÷ 30 | 20% of baskets |
Read those rows as one story, not four scores. In this invented example the line moved modestly, is well covered, returned more gross margin than the capital tied up in it, and appeared in a meaningful share of baskets — a profile you would misread as failing if you looked only at movement. For the margin mechanics underneath GMROI, see titanium drinkware profit margins for retailers.
Takeaway: a slow-moving premium SKU with strong GMROI and attach rate is doing its job — do not cut it on unit velocity alone.
Build your own baseline instead of borrowing one
Everything above is worthless without something to compare against, and the comparison has to come from you. Work through these steps once, then refresh them each quarter.
- Fix your definitions in writing. Window length, receipt basis, whether returns are netted, whether display units count. Ambiguity here produces numbers that argue with each other.
- Measure a full cycle before judging. Let the category run through one complete seasonal cycle so gifting and outdoor peaks sit inside the data rather than distorting a short sample.
- Set the baseline as your own median. Rank your titanium SKUs on each metric and take the middle of your range as "normal". That is your benchmark, and the only one describing your store.
- Judge each SKU against its role. A hero, a core run member and a specialist tail piece should not face the same figures — decide the expected profile for each role first.
- Re-baseline every quarter. As traffic, assortment and season shift, the median moves. A baseline set once and never revisited becomes the borrowed benchmark you were avoiding.
One structural factor helps: TAIC vessels are 99.8% pure titanium with no interior coating or liner, Ti-Anox colour that is an oxide layer rather than paint, and a limited lifetime warranty backed by 150+ patents, an R&D collaboration with the Chinese Academy of Sciences, and SGS test reports. Fewer returns and write-offs keep your numerators and denominators clean, which makes a baseline built on them worth trusting. To scope quantities against the figures you measured, apply to the Wholesale & Trade program.
Takeaway: your median is your benchmark — measure a full cycle, judge each SKU against its role, and re-baseline every quarter.
Frequently asked questions
What is a good sell-through rate for premium drinkware?
There is no universal figure, and any number quoted without your store's context is misleading. Premium drinkware turns slowly by design, so a healthy rate here would look weak on a fast-moving shelf. Set your own baseline from a full seasonal cycle of your own data and judge against that.
What window should I use to measure sell-through?
Use a window long enough to contain a realistic decision cycle for a considered high-ticket purchase, and use the same one every time. Quarterly suits most premium drinkware assortments. Whatever you pick, state it beside every figure — an unlabelled sell-through number cannot be compared to anything.
Should sell-through or weeks of supply drive my reorder?
Weeks of supply should drive it. Sell-through describes what already happened to a specific buy, while weeks of supply tells you how long before the shelf empties at your current rate — which is the question a reorder answers. Use sell-through to judge the buy, cover to time the next one.
How do I calculate GMROI for a titanium line?
Divide the gross margin currency the line generated by the average inventory at cost you held to generate it. Above one means the line returned more gross margin than the capital tied up in it. Use it to compare lines against each other within your own store rather than against outside figures.
Does attach rate matter for a high-ticket category?
Yes, and often more than unit velocity. Attach rate shows whether the category is appearing in baskets and pulling wider spend, which is how a slow-turn premium display earns its floor space. A rising attach rate can justify a line whose own unit count looks unexciting.
Can TAIC advise on order sizes once I know my numbers?
Yes — quantities, mix and terms are discussed case-by-case through our Wholesale & Trade channel. Bring your measured cover targets and role definitions to the conversation and we will scope an order against them, rather than applying a fixed minimum that ignores what your data actually shows.
These numbers are not hard to calculate; the discipline is refusing to compare them to figures that were never about your store. Fix your definitions, measure a full cycle, take your own median as the baseline, and read movement, timing, money and basket pull as one picture. To talk your figures through before the next buy, contact our team — and browse the coffee and tea collection for the specialty lines that often carry a stronger attach rate than their unit counts suggest.
