You just give us a shop's address. Every few hours we read its stock levels, and from the drops we work out how many units it sold and at what price. No plugins and no access to their admin panel: all of it comes from what the shop publishes itself.
Competitors' exact sales, worked out from the drops in their stock levels. Every product with its price and stock history. Plus a view of their marketing and their social media.
Press any of them and we will check it while you watch. Free, in a minute.
We detect the platform, count the products and confirm that we can read this shop's stock. You see the price after you have the proof that it works, and before anything is charged.
Every 2 to 12 hours we read the whole catalogue and the stock behind it, steadily and in order. The more often we read, the more precisely you can see what sold on which day.
Stock fell from 84 to 79: that is five units sold. Multiply by that day's price and you have revenue. A large rise in stock is a restock and a small one is usually a return; neither is a negative sale, so neither subtracts from the figure.
The same stock data answers three questions that three different people in a company keep asking.
A competitor's sales day by day, in units and in revenue. You can tell whether a weak week was the market or your shop alone.
A buyer does not have to guess. They can see which products and which sizes are selling elsewhere before placing their own order.
Alongside the number of units sold we show the likely reason: the advertising they are running right now, the newsletters they send, their search rankings and every price change.
Everything below comes from the same stock levels. None of it needs an integration, a plugin, or any involvement from the shop being monitored.
A day-by-day table of units and revenue. Click a day to see exactly what sold that day.
Every product and every variant separately: how many sold, how many are left, at what price. New arrivals and recently sold-out items come first.
Sizes, shortages, category value, restocks and price changes. Each one downloadable as CSV or PDF.
Sales broken down by store - a figure normally only their own head office has.
Creatives from the Meta, Google and TikTok libraries, and the competitor's newsletters: what they say, since when, to whom and with what reach.
Visibility, keywords and sessions, plus what the competitor gained or lost since the last measurement.
The history of every check: when, how many products, by which method, and whether the result is trustworthy.
One stream across every shop you monitor: sell-outs, restocks, new campaigns, sharp changes in visibility.
* The per-store breakdown only works for chains that publish stock for each location. The check states plainly whether this particular shop does.
Two example shops with their full stock and sales history, in the real panel. No sign-up, no card.
Market intelligence tools estimate revenue from website traffic. We read stock levels instead, which shows things traffic never can.
The rest of the market guesses revenue from visitor counts and an average order value. We count the units that left their stock and multiply by that day's price.
You see the campaigns a competitor is running right now and the sales from those same days. That is how you tell whether a campaign changed anything.
For chains that publish stock per location, we split sales across individual cities. You learn which of their stores the result is coming from.
Stock per variant means you can see that size 38 sold out in four days while size 44 has been in stock since March without selling. That is a ready-made buying list.
A clear rise in stock is a restock, as opposed to a single unit reappearing, which is usually a return. You see a competitor's delivery rhythm and what they reorder more of after a good season.
We record every price change next to the same day's sales. You can tell whether a discount increased sales or only reduced the margin.
The price follows three things: how large the catalogue is, how often we read it, and how hard the data is to get out of the shop. You are billed only for successful runs.
per day of watching a shop of up to 200 products - 2 reads every 12 hours.
| Products in the catalogue | every 12 hours | every 8 hours | every 4 hours | every 2 hours |
|---|---|---|---|---|
| up to 200 | $0.30 $9 / 30 days | $0.45 $14 / 30 days | $0.90 $27 / 30 days | $1.80 $54 / 30 days |
| 201 - 1,000 | $0.60 $18 / 30 days | $0.90 $27 / 30 days | $1.80 $54 / 30 days | $3.60 $108 / 30 days |
| 1,001 - 5,000 | $1.20 $36 / 30 days | $1.80 $54 / 30 days | $3.60 $108 / 30 days | $7.20 $216 / 30 days |
| 5,001 - 20,000 | $2.40 $72 / 30 days | $3.60 $108 / 30 days | $7.20 $216 / 30 days | $14.40 $432 / 30 days |
The number we price on is however many items the shop itself lists. In most shops that is products. In some, every size and colour is a separate item, which can be several times more than the product count you would read off their menu.
Full price list, up to a million products and beyond
These are starting prices, and they depend on how hard the stock is to read. You get the exact price for a specific address in 60 seconds, by clicking the button below. Several customers can watch one shop at the same time; if you would rather its data reached nobody else, exclusivity costs 99 USD a month.
Just type a competitor's address and see within a minute whether we can read its stock, how large its catalogue is and what monitoring it would cost per day. You pay only once monitoring starts, and only for the days on which a check succeeded.
We read at a few requests a second, spread over time - less traffic than one active customer generates. Most shops publish their current stock levels openly. We do not sign in, we do not place orders, we do not break into anything, and we read nothing beyond publicly available pages.
A drop in stock is a candidate for a sale, not proof of one. A run in which more than a quarter of the variants fall to zero at once is discarded entirely. A zero that stock later recovers from - 10, then 0, then 8 - is treated as a bad reading rather than as ten sales. And when a shop changes platform, we break the history at that point instead of recording its entire stock as sold.
The catalogue, prices and stock appear within 10 minutes to 3 hours of adding the shop, depending on its size. Sales come from the difference between two readings, so the first sales figure arrives after the next run.
As many as you need - each billed separately, per day of monitoring. Events from all of them collect in a single stream.
By default yes, and that is why the price is what it is: we read the shop once and share the cost between everybody monitoring it. You can reverse that. Exclusivity costs 99 USD a month, and while you hold it nobody else on SKUmio can monitor that shop or see reports about it. There is one condition: nobody else may be monitoring it already. You can buy it while adding the shop, or later in its settings, and give it up whenever you like.
Type an address. Within a minute we will prove that we can read its stock levels and work out its daily sales.
The check is free, with no account to create and no card to enter.