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It is 7:00 on Monday. Last week’s report is already in.

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Monday 8 September 07:00
Monday Report now

Mable, 1–7 Sep. Three things found, one already handled. Two need a yes.

  1. 1 Ad set 14: $1,900, no sales. Paused.
  2. 2 Linen shirt: out Thu. Reorder drafted.
  3. 3 Margin −2.1 pts. Fix proposed.
Pipelines 06:00

All four runs finished, 14,208 rows.

  1. 01

    Ad set 14 spent $1,900 and sold nothing. Paused.

  2. 02

    The linen shirt runs out on Thursday. A reorder is drafted.

  3. 03

    Margin is down 2.1 points. The cause is found and a fix proposed.

  1. Ask Mable · 1–7 Sep
    Which SKUs lost margin this month, and why?

    Three SKUs, one cause. Linen shirt −4.1 pts, wool coat −1.8, silk scarf −1.2. Ad spend doubled in July.

    Linen shirt at $36 on Amazon gets it back to ~35%. Want me to?

    From amazon
    Yes, Amazon only.

    Done at 09:12. $36 on Amazon, unchanged on Shopify. Report on Monday; undo if conversion drops over 8%.

    Undo
    Ask anything about the store…

    Ask · the question, the cause with its chart, the sources it read, and the price changed on Amazon only, with an undo.

    02 Any time

    Ask the whole store. Then let it act.

    Ask why, get the cause and the chart, say yes, and it is done on the channel you named, with an undo and a report next Monday.

  2. Ask Mable · 1–7 Sep
    I have $3,000 left this month. Ads, stock, or something else? Where does it do the most?
    Working it out · 4 s
    • Reading ad spend by set, last 30 days
    • Margin by SKU after ad cost
    • Stock cover by SKU against the supplier lead time
    • Comparing: another $3,000 on ads vs. $3,000 into the wool coat reorder

    So far: ads are past the point of return on two sets; the wool coat sells out in 11 days with 23 days of lead time.

    Ask anything about the store…

    Ask · one question, three sources read, one comparison still running, and what it has found so far.

    03 Any time

    Ask where the money should go.

    One question, and it reads every source before it answers. You watch it work, and it tells you what it has found while it thinks.

  3. 04 Day one

    Already built. We plug it in.

    The product exists. Connect your accounts, and the first report follows.

One seller, one season

A two-person clothing brand in the UK, selling on Amazon and Shopify.

01 Monday, before
  1. 01 Monday began with five tabs open, and a spreadsheet filled in by hand on Sunday night. No two of them agreed.
  2. 02 An ad set kept spending for three weeks on a shirt that had sold out. Spend and stock lived in different tabs, so nobody saw it.
  3. 03 The first sign of a stock-out was a customer asking when the linen shirt would be back.
  4. 04 Margin slipped for two months. Everyone had a theory. Nobody had the number.
02 What went in
  1. 01 Every channel copied into one store of data every night, on an account they own.
  2. 02 One report at 07:00 on Monday. Three findings, each with its cause and the money attached.
  3. 03 Watchers written in their own words, such as an ad set spending for three days with no sales, checked every morning.
  4. 04 One question box over the whole store. It answers, and on a yes, it acts.
03 Monday, now
  1. 01 The first Monday found the ad set with no sales. It was paused before nine.
  2. 02 Reorders now start from the report, days before the shelf is empty, not from a customer email.
  3. 03 A price change on one channel takes one sentence, and comes with an undo.
  4. 04 At handover the access was revoked. The data, the pipelines, and the reports are theirs.

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