Every figure below is measured daily from the shop's own records — not estimates, not promises. This is what happens when a shop stops watching stock by hand and lets Wezesha count every shelf, every day.
Figures from Beauty Square KE, Nairobi · Jan–Aug 2026.
A Nairobi beauty retailer running over 1,000 products across two branches replaced hand-watched reordering with a daily inventory system — cutting bestseller stockouts by about a third and clearing roughly 23% of its dead stock in the first tracked month, once it could finally see it.
January–May figures are reconstructed from the sales record — no shelf records existed then. Everything from June is measured daily from the store's own records.
| What we track | Before (reconstructed) | After (measured) |
|---|---|---|
| Bestseller shelves empty | ~16.6% in a typical week, while customers still wanted them | 11% weekly average (Jun–Jul). First full week 12.4%, down to 6.9% five weeks later |
| Worst weeks | Peaks above 35%; roughly 8 of 23 weeks over 20% | No week above 20%. One bad stretch neared 19% — including a week the sales feed broke; the system flagged it and refused to guess |
| The quiet sellers (B) | Good sellers nobody could watch daily sat empty 17–27% of every week. Nobody knew | Watched every day, split out next to the top sellers in the Monday email |
| Cost of a stockout | Never measured. No number existed | Now measured every week — each empty bestseller shelf carries a real lost-sales figure the owner can see and act on |
| Ordering | Instinct. No check on stock already on the way, so it was easy to order twice | A costed list. Every line priced and totalled, bestsellers first, minus what's on hand and already coming |
| Dead stock | Invisible. Cash frozen, no list, no number | Measured monthly and clearing — ~23% of frozen cash gone in the first tracked month (184 → 150 SKUs). Every dead item is C-class |
| The owner's time | Hours every week walking shelves, counting, building orders by hand. And the quiet sellers still slipped through | About 15 minutes. One email, Monday 6am. Three decisions. Done by 6:15 |
"The products the owner watched himself almost never ran out. Everything else did — and nobody knew."
Before June, the inventory system at Beauty Square was the owner. The famous products got watched by hand, and for those it worked — our reconstruction suggests the top sellers he tracked personally ran out very rarely.
But nobody can watch over a thousand products. The good-but-quieter sellers sat empty 17–27% of every single week. Nobody knew, because nothing measured a stockout. Ordering ran on instinct, transfers were sized by feel, and dead stock froze cash in silence. The bill was being paid every week — there was just no invoice.
Every shelf is now counted daily. Monday at 6am, one email arrives: the six-week trend with top sellers (A) and steady sellers (B) split out, what's empty with nothing on the way, what to order with the budget attached, and what to move from the warehouse. Three decisions. Done by 6:15.
The buy list works off the real selling rate — it only counts days the product was actually on the shelf, ignores one-off bulk buys and freak spikes, and subtracts what you have and what's already coming, so it never orders twice.
"An empty shelf used to cost 'something'. Now it has a number. A number you can see is a number you can fix."
First it made dead stock visible. Then it started clearing it. Once the slow movers were listed item by item and valued at cost, the shop could work a real clearance list — and in the first tracked month it cleared about 23% of the frozen cash (roughly 184 dead SKUs down to 150). One month of clearing so far, so it's early, but the direction is down and the list refreshes every month. The health check that matters most: the top sellers hold zero dead stock, checked every month, clean so far.
Not every week was pretty, and the record keeps the ugly ones. One stretch climbed toward 19%, including a week when the sales feed broke. The system caught it, refused to forecast on bad data, kept the last good plan, and told the owner.
We'd rather show you that week than hide it. One month of dead-stock clearing is early — but the direction is down, and it's measured, not promised.
Case study data: Jan–Aug 2026 · Beauty Square KE, Nairobi · A product by Simply Done Africa.
Wezesha Restock connects to your Shopify and POS, measures what stockouts and dead stock cost your shop, and hands you the Monday email. If it can't find trapped cash and unwatched stockouts in your data, you'll know within weeks — because it measures itself in front of you.
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