Which Hoodie Colours Deserve a Repeat? Why Raw Units Mislead
Black sold 1,800 units, grey marl 1,320 and pigment-washed charcoal only 540, so should most of the next buy of hoodie colours go to black? That is the situation in many trading meetings after the first full read of a season, and the answer depends on a question the raw numbers do not answer: how many weeks was each colour actually available to buy, and in which sizes?
This guide is for buyers at established UK and European retailers who already track sell-through. It sets out a four-step method for deciding which hoodie colours to repeat, reduce or discontinue and shows the arithmetic on an illustrative three-colour example. Every figure in the worked example is hypothetical; none is a benchmark or a market result.
A colour that sold out in three weeks and a colour that stayed in stock for twelve cannot be ranked on total units. Rank them on rate of sale per week of real availability, then test that ranking against returns, size breaks and the stock you would be left holding. The method below does this in four steps, each with a check to pass before the next is trusted.
From raw sales to a colour decision
- 1Compare by colour and sizeRead sell-through for every colour and every size. Look for size breaks and a curve that sold out in the middle sizes.
- 2Normalise for availabilityCount the weeks each colour was actually on sale in the core sizes and divide units sold by those weeks.
- 3Check returns and markdownNet off returns, read the reasons and size the stock you would still hold at season end.
- 4Allocate the repeatBuild the quantity from demand, seasonality, safety stock and usable stock, and stage it where the evidence is thin.
Illustrative workflow. Thresholds and read dates should be agreed with your trading team before launch.
The sections that follow take the steps in turn, and a worked example then shows the whole method on one set of numbers.
What You Need Before You Compare Hoodie Colours
A fair comparison needs more than a sales total. For each colour of the same style, price point and window, pull units received, units sold, closing stock, weekly sales, weeks available in the core sizes, returns with reason codes, and any promotion that touched one colour but not another.
The table below defines the measures used in this guide. Definitions vary by retailer, especially the sell-through denominator, so agree which version your trading reports use and keep it fixed when comparing colours.
The KPIs used to compare hoodie colours
| KPI | Formula | What it tells you | Where definitions vary |
|---|---|---|---|
| Colour sell-through | Units sold divided by units received over the same period | How much of the colour bought has been sold | Some teams divide by units available (opening stock plus receipts) |
| Weekly rate of sale (normalised) | Units sold divided by effective weeks on sale | Demand per week of real availability, so colours can be ranked fairly | Effective weeks can be counted at colour level or core-size level; stricter is better |
| Stock cover | Available stock divided by forecast weekly sales | How many weeks the remaining stock will last | State whether forecast is the recent rate or a plan, and whether on-order stock is included |
| Returns rate | Units returned divided by units sold | Whether sales are sticking, and why they are not | Online and store returns are often reported separately; keep the channel mix the same for each colour |
| Markdown exposure | Closing stock multiplied by the margin you expect to give up in clearance | The cost of being wrong on depth | Illustrative per-unit give-up is a planning assumption, not a result |
Definitions are standard planning formulas. Check how your own reporting system calculates each one before comparing figures across teams.
Keep the colour-level and size-level views side by side. Colour decisions that ignore the size curve usually mistake a size problem for a colour problem.
Step 1: Compare Hoodie Colour Sell-Through by Colour and Size
Start at the size level, not the colour total. A colour can look healthy at 88 per cent sell-through in aggregate while its middle sizes sold out weeks before the end of the window and its extreme sizes barely moved. The aggregate hides two problems: lost sales in the sizes that sold out, and stock risk in the sizes that did not.
Read the size curve for each colour
The table below shows an illustrative size breakdown for grey marl from the worked example. The first buy gave generous weight to the smallest and largest sizes, while customers bought the middle of the range.
Illustrative size curve: grey marl hoodie
| Size | Received | Sold | Closing stock | Size sell-through |
|---|---|---|---|---|
| XS | 100 | 40 | 60 | 40% |
| S | 250 | 230 | 20 | 92% |
| M | 400 | 400 | 0 | 100% |
| L | 400 | 400 | 0 | 100% |
| XL | 250 | 230 | 20 | 92% |
| XXL | 100 | 20 | 80 | 20% |
| Total | 1,500 | 1,320 | 180 | 88% |
Hypothetical figures for illustration only. Sales in M and L understate demand because both sold out.
Two things stand out. M and L reached 100 per cent size sell-through, so demand was cut off by availability and the true demand share for those sizes is higher than the sales share shown. And 140 of the 180 unsold units are XS and XXL, so the headline stock figure overstates what is usable. If the shortfall is a size problem, fix the curve before you decide the colour is weak.
Step 2: Normalise for Weeks on Sale and Stockouts
Weeks-on-sale normalisation answers one question: how fast did this colour sell while a customer could actually buy it? The working formula is weekly rate of sale equals units sold divided by effective weeks on sale, where an effective week is a week in which the colour was available in the core sizes. Define the core sizes before looking at the data, so the definition cannot be tuned to flatter a colour.
In a stockout week sales stop because stock stops, so the normalised rate measures demand only while stock lasted. Use it to rank colours and size a first repeat, then confirm it against the next read. Where the effective window is short, treat the rate as a hypothesis and stage the repeat.
Bias also runs the other way. A colour heavily promoted in its in-stock weeks may show a rate that falls away once promotion ends, so check weekly sales for a launch spike and compare against a colour that had no extra exposure.
Worked Illustration: Black vs Grey Marl vs Pigment-Washed Charcoal
The example below applies the method to three colours of one hoodie style. Every input is hypothetical and chosen to show the arithmetic, not to suggest how any real colour performs. The assumptions are: the same style, fit and retail price for all three colours; a 12-week selling window; 4,500 units received in total across the three colours; core sizes defined as S to XL; black as a fabric-dyed core colour, grey marl as a melange (marl) fleece, and charcoal as a garment-dyed, pigment-washed finish; and returned units not resold within the window.
What the raw numbers say
Ranked on total units sold, black wins comfortably and charcoal looks like the weak colour.
Illustrative first read: raw units by hoodie colour
| Colour | Units received | Units sold | Closing stock | Sell-through (sold divided by received) | Rank on raw units |
|---|---|---|---|---|---|
| Black | 2,400 | 1,800 | 600 | 75% | 1 |
| Grey marl | 1,500 | 1,320 | 180 | 88% | 2 |
| Pigment-washed charcoal | 600 | 540 | 60 | 90% | 3 |
| Total | 4,500 | 3,660 | 840 | 81% (3,660 divided by 4,500) | - |
Hypothetical figures for illustration only; not market data or supplier results. Closing stock equals received minus sold. Sell-through uses units received as the denominator.
Raw units sold by colour
Units sold over 12 weeks
Illustrative values from the worked example. Black has about 49 per cent of all units sold (1,800 of 3,660), grey marl about 36 per cent and charcoal about 15 per cent.
On this view black looks like the bestseller and charcoal a candidate to drop. Now correct for availability.
What the normalised weekly rate says
Grey marl ran out of stock in the core sizes after week 8 and charcoal after week 3. Black was in stock throughout. Dividing units sold by effective weeks on sale reverses the ranking.
Illustrative normalisation: units per effective week on sale
| Colour | Weeks in window | Stockout weeks (core sizes) | Effective weeks on sale | Units sold | Weekly rate (sold divided by effective weeks) | Rank on weekly rate |
|---|---|---|---|---|---|---|
| Black | 12 | 0 | 12 | 1,800 | 150 | 3 |
| Grey marl | 12 | 4 | 8 | 1,320 | 165 | 2 |
| Pigment-washed charcoal | 12 | 9 | 3 | 540 | 180 | 1 |
Hypothetical figures for illustration only. Simplification: all units are divided by effective weeks, including a small number of extreme-size sales made after the core sizes sold out. A stricter version works size by size.
Weekly rate of sale by colour
Units per effective week
Illustrative values from the worked example (units sold divided by effective weeks on sale). The range average is 165 units a week, the mean of the three rates.
The order has flipped. Charcoal sold fastest while it was available, but its window is only three weeks, so its rate is the least reliable of the three. Black has the most stable read and the lowest rate. The raw view would have steered most of the repeat to black; the normalised view weakens the case for black and strengthens it for grey marl and charcoal.
Step 3: Study Returns and Markdown Exposure by Hoodie Colour
A colour that sells fast and comes back is not a winner. Net the returns off before ranking, read the reasons, and size the stock you would be left holding. Returns by colour often have a specific cause: shade not matching product photography, fit on one construction, or a finish that changes after the first wash.
Illustrative returns, net rate, stock cover and markdown exposure
| Colour | Units sold | Units returned | Return rate (returned divided by sold) | Net weekly rate | Closing stock | Observed stock cover | Illustrative markdown exposure |
|---|---|---|---|---|---|---|---|
| Black | 1,800 | 144 | 8.0% | 138.0 | 600 | 4.0 weeks | GBP 7,200 |
| Grey marl | 1,320 | 66 | 5.0% | 156.8 | 180 | 1.1 weeks | GBP 2,160 |
| Pigment-washed charcoal | 540 | 27 | 5.0% | 171.0 | 60 | 0.3 weeks | GBP 720 |
Hypothetical figures for illustration only. Net weekly rate is (sold minus returned) divided by effective weeks, rounded. Stock cover is closing stock divided by the gross weekly rate (600 divided by 150, 180 divided by 165, 60 divided by 180). Markdown exposure assumes GBP 12 of margin given up per unsold unit, an assumed planning figure. Grey marl cover is flattered by 140 unsold XS and XXL units.
Black carries the most exposure here: the highest return rate, four weeks of cover and 600 units still to sell, an illustrative GBP 7,200 at the assumed give-up. Net of returns the ranking holds: charcoal 171.0, grey marl 156.8, black 138.0 units a week.
Read stock cover with care. A figure near zero says the colour was bought too thin, not that it is healthy, while several weeks of cover on a slow colour signals markdown risk. As a lost-sales sense-check, if the charcoal rate of 180 had held through its nine stockout weeks the unmet demand would be 1,620 units, and at half that rate 810. These show scale, not forecasts, because launch demand rarely persists at full strength.
Step 4: Allocate Repeats from Demand and Seasonality
Once the ranking survives the returns check, build every repeat quantity from the same formula so the colours are treated consistently. Repeat quantity equals forecast weekly rate multiplied by selling weeks, plus safety stock, minus usable stock, where forecast weekly rate equals net weekly rate multiplied by a seasonal index and a confidence factor.
The illustration assumes the repeat covers eight selling weeks after it lands, a seasonal index of 1.1 for all three colours (a hypothetical lift as the weather turns colder), two weeks of safety stock, and a confidence factor of 1.0 for black and grey marl but 0.6 for charcoal, because its read rests on three weeks of a trend-led finish. Usable stock counts core sizes only. Choose your own values from your calendar and lead times; our guide on when to reorder a bestseller covers the lead-time side.
Illustrative repeat quantity by hoodie colour
| Colour | Net weekly rate | Forecast weekly rate (x 1.1 x confidence) | Demand over 8 weeks | Safety stock (2 weeks) | Usable stock | Calculated repeat | Indicative repeat (nearest 100) |
|---|---|---|---|---|---|---|---|
| Black | 138.0 | 151.8 | 1,214 | 304 | 600 | 918 | 900 |
| Grey marl | 156.8 | 172.4 | 1,379 | 345 | 40 | 1,684 | 1,700 |
| Pigment-washed charcoal | 171.0 | 112.9 | 903 | 226 | 20 | 1,109 | 1,100 |
Hypothetical figures for illustration only. Usable stock is core-size stock: all 600 for black, 40 for grey marl (S and XL from the size table), and an assumed 20 for charcoal. Components are rounded to whole units; calculated repeat uses unrounded values.
Compare the result with the first buy of 2,400 black, 1,500 grey marl and 600 charcoal. Weight shifts away from black and towards grey marl, which should be built on a revised size curve with more weight on S to XL. The charcoal calculation of 1,100 is almost double its original buy, exactly where staging is wise: commit a first tranche now and release the rest after the next read.
Repeat, Reduce or Discontinue: Decision Rules and the Evidence That Would Change Them
Agree decision rules before launch so the call is not argued colour by colour mid-season. The illustration compares each colour with the range average weekly rate of 165 units. The thresholds are examples for the worked case, not recommendations; set your own to suit your margin structure and lead times.
Illustrative decision rules applied to the three colours
| Colour | Weekly rate versus range average of 165 | Return rate | Decision | Evidence that would change it |
|---|---|---|---|---|
| Black | 150, which is 91% of average | 8.0% | Reduce depth, keep availability in core sizes | A lower return rate after a fit or shade fix supports a larger repeat; a further fall in rate supports a smaller one |
| Grey marl | 165, which is 100% of average | 5.0% | Repeat with a revised size curve | S to XL selling out again would show the repeat was too thin |
| Pigment-washed charcoal | 180, which is 109% of average | 5.0% | Repeat in stages: first tranche of 500, rest after the next read | A second clean read at or above average releases the remainder; a drop toward 60% of average stops it |
Hypothetical rules and figures for illustration only. Example rules: repeat when the weekly rate is at or above average and returns are within an agreed ceiling; reduce depth between 60% and 100% of average; discontinue below 60% of average over two reads, or when returns exceed the ceiling and cannot be fixed.
None of the three colours meets the example discontinue rule, which is reserved for colours that fail on rate across more than one read or whose returns cannot be fixed. A staged first tranche is where a test quantity helps: our guide to test and scale clothing manufacturing explains the model, and 500 pieces is a proposed starting point where commercially and technically feasible, not a fixed minimum.
Why Dye Method Changes the Risk of Repeating a Colour
The same demand signal carries different supply risk depending on how the colour is made. A repeat is a new production run that must match the shade, hand and wash the customer already bought. Fabric-dyed solids, melange fleece and garment-dyed pigment finishes behave differently when repeated, so the difference should enter the allocation as a risk factor. Our guide to fabric dyeing methods explains the processes.
Indicative repeat risk by colour construction
1 dot = lower repeat risk, 5 dots = higher repeat risk
| Black (fabric-dyed) | Grey marl (melange) | Charcoal (pigment-washed) | |
|---|---|---|---|
| Shade match to the approved standard | ●●●●● | ●●●●● | ●●●●● |
| Garment-to-garment variation | ●●●●● | ●●●●● | ●●●●● |
| Effort to approve a repeat before bulk | ●●●●● | ●●●●● | ●●●●● |
Indicative ratings for a typical case, not laboratory results. Higher means higher repeat risk. The assumed constructions vary by factory and programme, so confirm for your own product.
Melange fleece depends on the fibre blend ratio being reproduced, and pigment-washed finishes depend on the wash recipe and process control, so the approved sample, shade band and pilot bulk matter far more than for a solid. The controls are in our guide to pigment- and acid-washed hoodies. Add shrinkage and colourfastness checks after wash, as described in our garment testing guide, because a repeat that shifts in shade or size can create the returns you were trying to avoid.
Common Mistakes When Judging Hoodie Colours
Most poor colour decisions come from the same few shortcuts. Check your own process against the list below before the next trading meeting.
Checks before you repeat, reduce or discontinue a colour
- Rank by weekly rate on effective weeks on sale, not by total units sold.
- Net off returns and read the return reasons by colour before ranking.
- Treat any rate built on a short effective window as a hypothesis and stage the repeat.
- Check the repeat is feasible on the dye method before committing the quantity.
- Keep one sell-through denominator across every colour and report.
Use as a pre-meeting checklist. Adapt it to your own trading calendar and reporting system.
Keep every colour comparison within one style and one price point. When the question is which style, rather than which colour, deserves more depth, our guide on which styles deserve a bigger buy covers the style-level read.
The Decision, the KPI to Watch and the Question to Take Into Your Next Meeting
The decision from the worked example is staged: reduce the depth of black while keeping core-size availability, repeat grey marl on a revised size curve, and release the charcoal repeat in tranches against a second read. Apply the same logic to your own hoodie colours: rank on weekly rate, test against returns and markdown exposure, then size the repeat.
The KPI to watch first is the weekly rate of sale on effective weeks, supported by colour sell-through, stock cover and returns rate. Change the decision if a restocked colour sells at a lower rate than before, if returns rise after a shade or finish change, or if cover stretches beyond the weeks left in the season. For the wider hunt for new winners, see how to identify the next bestselling hoodie.
Looking at your last hoodie season, which colour would change rank if you replaced total units with units per week of true availability, and do you know the answer today or would it take a rebuild of the data?
How Ruhrose Approaches Hoodie Colours
Ruhrose develops and produces hoodies, fleece, jersey, denim and woven casualwear in Bangladesh, with UK buyer support. For hoodie colours we sample before bulk, agree a shade standard and, for pigment or wash finishes, a pilot approval before the repeat. Where a buyer wants to read colour demand before committing depth, the test-and-scale approach is a risk-reduction model, not a risk-free one, and a test quantity of around 500 pieces per style and colour is a proposed figure where fabric, dye, trims and the factory allow it. It is not a guaranteed minimum. If you are weighing a colour programme, share the style and the read dates through our custom hoodie manufacturer page and we will say what is workable.