Returns season: the January plan

The shape of the wave

Returns after a peak season do not arrive evenly. They cluster, typically starting a few days after the holidays, building over a week or two, and then tailing off over the following month.

The exact timing depends on your returns window and your customers, and the shape is consistent enough to plan around: a quiet few days that feel like relief, then a volume of inbound that lands on a team that has just finished its hardest month.

That sequencing is what makes returns season difficult. It is not the volume in isolation; it is the volume arriving when everyone is tired and the temporary help has gone.

Four decisions to make in December

All of these are easier to decide before the wave and nearly impossible to decide well during it.

Who owns returns in January. One name. If it is shared across whoever is free, it becomes nobody's and the backlog grows quietly.

What gets refunded without inspection. Below a certain value, inspecting an item costs more in labour than the item is worth. Setting that threshold in advance removes a decision from every single return.

What happens to returned stock. Back to sellable, discounted, or written off, and who decides. Returns that pile up in a corner awaiting a decision are the most common January failure, and they block the physical space you need.

What you tell customers about timing. If refunds will take five working days in January rather than two, say so on the returns page before the season starts. A stated timeframe prevents most chasing messages.

The message that prevents the second contact

Most returns generate more customer contact than they need to, and the cause is silence at two specific moments.

When the return arrives. A short acknowledgement that you have it and when the refund will be processed. Without this the customer does not know whether it arrived, and a meaningful share will ask.

When the refund is issued. Including the fact that their bank may take a few days to show it, which is the single most common follow-up question and costs one sentence to pre-empt.

Two automatic or templated messages remove a large share of January's inbound. Both are worth setting up in December, when there is time to write them properly.

Reading the returns you get

Returns season is the best data you will get all year about your products, and most stores process it without looking at it.

Record a reason for every return, using a small fixed list rather than free text. Four or five categories is enough: wrong size, not as described, damaged, changed mind, arrived late.

The value shows up in aggregate. One product returning at several times the rate of everything else is telling you something specific: sizing that runs small, photography that misleads, packaging that fails in transit. Each of those is fixable, and none is visible from individual returns.

Fifteen minutes reading the categorised list in February is one of the highest-return exercises in the year, and it is only possible if somebody recorded the reasons in January.

A high return rate on one product is not a returns problem. It is a product page problem, a sizing problem, or a packaging problem, and it is much cheaper to fix than to keep processing.

Protecting the team through it

January follows the hardest month of the year, and the emotional register of returns work is different from fulfilment: it is repetitive, occasionally involves unhappy customers, and produces no visible progress.

Two things help. Batch it rather than interleaving returns with everything else, because context switching between processing returns and answering pre-sale questions is more tiring than either alone. And make the progress visible, even crudely, because a backlog with no visible end is demoralising in a way the same volume with a countdown is not.

If people took leave immediately after peak, check that returns are not landing entirely on whoever stayed. That distribution happens by accident and produces resentment that outlasts the season.

What to change before next year

Whatever you learn in January should be captured while the wave is still happening, not in a retro three months later.

Keep a running note through the month: which products caused disproportionate returns, which customer questions kept recurring, and where the process stalled. It takes seconds each time and produces something specific to act on.

Feed it into the same place as your post-peak retro findings, so there is one list rather than several, and set the reminder to read it before next peak rather than after.

The physical side

Returns take up space, and space runs out faster than anyone plans for because the volume arrives while your storage is still full of peak stock.

Decide three things in December. Where returns go when they arrive, which should be a defined area rather than wherever there is room. How long they can sit there before a decision is required. And who clears it, by name, on which day.

The failure is not dramatic. It is that returned items accumulate in a corner, nobody wants to make the resell-or-write-off call, and by February you have a pile of stock that has been unsellable for a month while occupying the space you need for new inventory.

A weekly clear-out with one named owner prevents it entirely, and it is much easier to schedule in advance than to introduce halfway through the wave.

Refund timing and cash

Worth thinking about before January, because the cash effect is real for a small store.

Refunds cluster in the same weeks as your quietest trading, so money goes out while less comes in. A store that spent heavily on peak stock can find January genuinely tight, and the refund wave is the part that gets forgotten in the planning.

Two things help. Estimate the likely refund volume from last year's rate applied to this year's peak revenue, so the number is not a surprise. And process refunds promptly rather than batching them to delay the outflow: delaying refunds to manage cash generates customer contact, chargebacks and reviews that cost considerably more than the few days of float were worth.

What good looks like by February

A short list to aim at, because "get through January" is not a target anybody can act on.

No unprocessed returns older than a week. A categorised list of return reasons, read once, with two or three product-level actions taken from it. The returns area empty. And a short note of what to change before next peak, filed with the retro findings rather than separately.

None of that is difficult. All of it requires deciding in December who owns it, because in January the people who would have organised it are the people recovering from December.

The December checklist

Six things to settle before the wave, each taking minutes now and impossible to arrange well in January.

Name who owns returns. Set the no-inspection value threshold. Decide where returns physically go and who clears the area weekly. Write the two customer messages. Publish your January refund timeframe. And estimate the refund volume so the cash effect is not a surprise.

Every one of these is a decision rather than a task, which is why they are cheap in December and expensive in January, when the people who would make them are recovering from December.

Returns as a signal about peak

One last use for the categorised list, which most stores never make.

Compare your return rate on products bought during peak against the same products bought at other times. If peak purchases return at a noticeably higher rate, the cause is usually gift buying rather than anything about the product, and that is worth knowing because it changes what you would fix.

A gift-driven return rate points at sizing guidance and gift receipts rather than at the product page. A rate that is high year-round points at the product itself. Same number, entirely different response, and telling them apart takes ten minutes with data you already have.

Common questions