There's no reliable published benchmark for wholesale reorder rates on Faire specifically — the industry figures that exist are almost all DTC consumer retail (subscription boxes, general e-commerce), and comparing a wholesale account's reorder behavior to a consumer's repeat-purchase habit isn't a fair comparison. Chasing someone else's number is less useful than knowing your own.
Calculate it directly instead: of every store whose first order was placed more than twelve months ago, what share placed a second? That single ratio, tracked over time, says more than any outside benchmark would.
Repeat-purchase research is a real, well-covered field — it's just aimed at consumer retail. Subscription boxes, general e-commerce, direct-to-consumer brands: these have published, well-studied repeat-purchase figures because the data is easy to get and the business model depends on it. One agency dataset of 156,110 direct-to-consumer customers, for instance, reports an 18.8% repeat rate over a 365-day window, ranging from 22–44% for consumables down to 7–18% for durables — the kind of segmented, sample-sized figure that simply has no wholesale equivalent. Faire doesn't have a comparable body of research, and that gap isn't an oversight: genuinely comparable B2B wholesale figures don't exist publicly in a form worth citing.
The deeper reason a DTC number wouldn't transfer anyway is that a shop owner and a consumer are making different decisions on different timelines. A consumer reorders when they personally run out of something and feel like buying more. A store reorders when shelf space frees up, cash flow allows it, the season turns over, or someone remembers to place the order at all — reasons that have a lot more to do with running a small business than with wanting more product. Why don't wholesale buyers reorder? goes through those reasons in more detail, and none of them map cleanly onto a consumer's repeat-purchase decision.
So a DTC benchmark isn't a rough approximation that's better than nothing — it's a different phenomenon wearing the same label. Citing it as a wholesale stand-in would create false confidence in one direction or false alarm in the other, and there'd be no way to tell which.
The calculation itself is simple. What takes discipline is picking a consistent cutoff and sticking to it, so the number means the same thing every time you check it.
The twelve-month cutoff matters more than it looks like it should. A store that ordered two months ago hasn't reordered yet, but it also hasn't had a full year to — including it in the denominator makes the rate look artificially low for reasons that have nothing to do with your retention. Restricting the denominator to stores old enough to have had a real chance is what makes the ratio comparable from one quarter to the next.
The single most useful thing about this number isn't the number itself — it's the series. One reorder rate tells you almost nothing. Four consecutive quarters of it moving in one direction tells you something real about whether retention is getting better or worse.
Even without a published figure to compare against, there's a shape you can check your own data against: a wholesale reorder curve should be front-loaded. Of the stores in any cohort that are ever going to place a second order, most of them do it relatively soon after the first — not spread out evenly across the following year.
That's worth checking directly, separately from the overall rate. Plot how long it took each reordering store to place its second order, and look at where the bulk of that distribution sits. If it's clustered early, that's the expected pattern. If it's flat — if stores are just as likely to reorder in month ten as month two — or if it's back-loaded, with most second orders showing up late, that's a more interesting signal than the headline rate is.
A flat or back-loaded curve usually points at something operational: follow-up isn't happening early enough, or it's happening on a fixed schedule that doesn't match when stores are actually ready to reorder. A front-loaded curve with a low overall rate is a different problem than a flat curve with the same rate — the first is about volume, the second is about timing.
No, and treating it that way is one of the more common ways this metric gets misused. What counts as a normal reorder rate depends heavily on what you sell. A consumable, everyday item at a low price point should reorder more often than a high-ticket item bought once a season. A brand two years into wholesale will have a different-looking rate than one six months in, independent of how well either is doing.
A low number is a prompt to ask why, not a verdict on its own. Sometimes the answer is a real retention problem. Sometimes it's a sell-through problem, or a friction problem, or simply a category where stores restock twice a year rather than monthly — the same reasons covered above, including which of them are actually fixable with a follow-up versus which ones aren't.
What's actually diagnostic is the trend, not the level. A rate that's drifting down over several quarters, with nothing else in the business changing, is worth investigating. A flat rate that's simply lower than you hoped isn't automatically a crisis — it might just be what normal looks like for this product.
If you don't have twelve months of order history yet, skip the calculation for now rather than forcing it on a partial cohort. A denominator full of stores that haven't had a fair chance to reorder will understate the rate for reasons that have nothing to do with retention, and an early number like that is more likely to be acted on wrongly than not acted on at all.
If you find a DTC or general e-commerce repeat-purchase figure somewhere and you're tempted to hold your own rate up against it, don't. It isn't measuring the same behavior, and the comparison will make you either falsely alarmed or falsely comfortable — there's no way to know which without a wholesale figure that doesn't exist.
And even your own number, once you have it, doesn't answer everything by itself. A high reorder rate on thin margins can matter less than a lower rate on healthy ones — the reorder rate tells you whether stores come back, not whether it's profitable when they do. If you haven't looked at the margin side of that question, what's a normal margin for a Faire seller? covers the other half of the picture. Treat the reorder rate as one input into a bigger decision, not a score to optimize on its own.
Last updated August 2026. Written by the maker of FaireSight, a retention tool for brands selling wholesale on Faire. Not affiliated with Faire.