brume orders data to 15 Oct · built 16 Oct 19:13 UTC
Orderslast 12 months · monthly
1,441
+459% vs previous 30 days · 258 · 48 / day by New / Repeat
Orders
1,441
+459% · 258 prev New customers
1,144
+747% · 135 prev Net revenue
$118,354
+509% · $19,449 prev Gross profit
$80,904
+528% · $12,887 prev Units
3,418
+448% · 624 prev AOV
$82.13+9%
AOP
$56.14+12%
Units / order
2.4-2%
GP / unit
$23.67+15%
Rev / unit
$34.63+11%
GP margin
68.4%+3%
Refunds
$2,232+470%
Refund rate
1.9%-6%
Orders by New / Repeat NewRepeat
New / Repeat
| Orders | vs prev | 12 wk | |
|---|---|---|---|
| New | 1,144 (79%) | +747% | |
| Repeat | 297 (21%) | +141% | |
| Total | 1,441 | +459% |
Pace +1,199 vs prev since day 11 · on pace 1,491 nowprevLY
Mix shiftshare · prev → now
New
+27.1 pt
Repeat
−27.1 pt
0%43%86%
Where × whatshare of column
US1,299
UK30
Europe109
Rest of World3
New
85%
39%
67%
Repeat
15%
100%
61%
33%
How to use Click a metric card — the whole page (hero, timeline, table, pace, mix, where×what) switches to that metric. Click a bar in the timeline, or a row in the breakdown table — the page filters to that day / week / month or segment, PowerBI-style. Click again, or the chip, to release. Breakdown picks what everything is split by: New / Repeat, category, territory, age band or gender. Age band and gender are the ordering customer's (age on the order day); age bands always read 18-24 → 65+, everything else is biggest first. Total / Breakdown affects the timeline only. Grain (Auto / Day / Week / Month) sets the timeline's bars. Day works for ranges up to 6 months (185 days); past that the chip is muted, Auto picks Week or Month, and a Day choice falls back to Auto. Sparklines in the KPI cards are the last 12 months (monthly totals, latest month highlighted) regardless of the period; the table sparklines are the last 12 weeks. Deltas compare with the same-length period just before. Orders / New customers are distinct counts. By category they mean orders containing that category (as in Power BI): an order with two categories sits in both rows, so rows can add up to more than the Total, which is always the true count. A Product filter counts orders containing that product.