Guide
What is sell-out data?
Updated 13 October 2026
Sell-out data is the record of what your products sold to shoppers through the retailer's tills: units and rand value, for every product, in every store, usually for every day. It is the closest thing a supplier has to seeing the shelf from the inside.
Sell-out and sell-in are not the same thing
Sell-in is what you sold to the retailer: your invoices, your orders, your deliveries to their distribution centres and stores. Sell-out is what the retailer then sold to shoppers. Most suppliers know their sell-in to the last unit, because it is their own data. Sell-out lives in the retailer's systems.
Sell-in
- What the retailer bought from you
- Comes from your own invoices and orders
- Tells you what you shipped
- Can look healthy while stock piles up in stores
Sell-out
- What shoppers bought from the retailer
- Comes from the retailer's tills, shared with you
- Tells you what actually sold, where and when
- Shows the problems while they can still be fixed
The gap between the two is where the trouble hides. Strong sell-in with weak sell-out means stock is building up in stores and will come back as returns or markdowns. Weak sell-in with strong sell-out means shelves are running empty and you are losing sales you never see.
Where sell-out data comes from in South Africa
Most of the big South African retail groups share sell-out data with their suppliers, usually through a supplier portal or a scheduled data feed. Some send it daily, others weekly. Most also send stock on hand, so you can see what is sitting in each store as well as what sold.
Every retailer does it differently. Each has its own portal and login, its own file layout, its own product codes instead of your barcodes and item numbers, and its own store names. Some charge suppliers for access. A supplier selling through ten retailers ends up with ten different versions of the truth.
What suppliers use sell-out data for
- Tracking growth: week, month and year to date against the same period last year, by product, channel, region and store.
- Finding out-of-stocks: stores where a line that normally sells has stopped, because the shelf is empty.
- Spotting phantom stock: the system says there is stock, but nothing has sold for weeks, so it is probably not on the shelf and the store will not reorder.
- Measuring days of cover: how long the stock in each store will last at the current rate of sale.
- Checking ranging: whether the stores that should carry a product actually do, and sell it.
- Judging promotions: whether a promotion grew sales or just borrowed them, and whether stock ran out halfway through.
- Directing the field team: sending reps and merchandisers to the stores where a visit will make the most difference.
- Preparing for buyer meetings: walking in with the retailer's own numbers, cleaned and compared.
Why it is harder than it sounds
The data is big. Daily sales for a few hundred products across a few thousand stores runs to hundreds of thousands of rows every day, per retailer. It arrives in different shapes, with codes that do not match yours, and history that has to be kept to compare against last year. Spreadsheets buckle under it, and the person maintaining them spends Monday rebuilding last week instead of acting on it.
The work that makes sell-out data useful is the unglamorous part: collecting every feed on time, matching every retailer's product and store codes to your own master data, adding the things the retailer does not know (your categories, your ranging, your promo calendar), and joining sales to stock so the gaps show up.
Sell-out data and market data
Retailer sell-out data covers your own products, in every store of that retailer, exactly as they sold. Market research data, such as panels and retail audits, estimates the whole category, including your competitors, from a sample. They answer different questions: sell-out tells you where to act store by store, market data tells you your share. Many suppliers use both.
How OuterJoin helps
We collect sell-out and stock data from the retailers you supply, clean it, match it to your own products and stores, and deliver it the way each part of your team needs it: online dashboards for managers, store reports for the field team, scheduled Excel reports for the people who live in spreadsheets, and bespoke analysis when a question needs an analyst.
Common questions
- Is sell-out data the same as POS data?
- Broadly, yes. Point-of-sale (POS) or scan data is the raw record from the tills. Sell-out data is that record as the retailer shares it with suppliers, usually summarised by product, store and day.
- How often is sell-out data updated?
- It depends on the retailer. Many send it daily, some weekly, and a few with a delay of a week or more. Stock on hand often follows a different schedule from sales.
- Do suppliers have to pay for sell-out data?
- Some retailers charge suppliers for access to their data, others include it. Either way, the cost of the data is small next to the cost of not using it.
- Can sell-out data show out-of-stocks?
- Yes, when it comes with stock on hand. A store with zero stock on a line that normally sells is out of stock. A store showing stock that has not sold for weeks may have phantom stock: the system count is wrong and the shelf is empty.