The traditional ‘Big Four’ UK supermarkets (Asda, Morrisons, Sainsbury’s and Tesco) provide data and reporting tools for their suppliers to help them to understand their trading performance “but each varies in the grain, scope and mechanisms they use.” These are commonly referred to as ‘retailer portals’ and all provide some tools and data free of charge to their suppliers.
Free data is typically limited to a supplier’s own performance i.e. you will only be able to see how your products are selling, where they are stocked, and how they are moving between depots and stores – you will not be able to see the same for competitor products (for that you will need to purchase ‘category data’ from the likes of NielsenIQ or Circana).
You will also not have access to shopper insights that the retailers generate from their loyalty card schemes; for these, you will need to purchase from Quantium (Asda), Circana (Morrisons), Nectar360 (Sainsbury’s) or dunnhumby (Tesco).
- Understand how your products sell at different price points, across different regions and at different times of year – helping you to plan growth, promotions and new product development;
- Identify issues in-store availability that are artificially depressing demand for your products – helping you to identify, illustrate and communicate with your retail counterparts so that you can work together to fix day-to-day issues and meet shopper demand;
- Develop a ‘trusted partner’ relationship with your retailer counterparts as they come to recognise that you have your finger on the pulse of your joint trading performance and are willing and able to identify and fix issues; this often leads to improved opportunities to propose new product listings, promotional activities and expanded listings across more of their store estate
Which metrics are available in free supermarket data?
Whilst each supermarket provides its own unique dataset, there’s a lot of commonality between them. All provide a daily feed that summarises detailed item-level performance from the previous day, including:
- Store Sales; value (£) and volume (units)
- Store Stock (closing and/or opening units)
- Inbound Store Service; units expected, units received
- Depot Stock (closing and/or opening units)
- Inbound Depot Service; cases expected, cases received
In addition, each provides some/many of the following:
- Store Availability (an indicator of the presence of an item in store)
- Planned Distribution (an indicator of which stores have a planogram that includes the item)
- Store Markdown; value (£) and volume (units) at reduced price (e.g. ‘yellow stickers’)
- Store Waste; value (£) and volume (units)
Each supermarket system (retailer portal) uses its own conventions for naming. For example:
- [Inbound] Store Service is also referred to as [outbound] Depot Service Level (what is ‘inbound’ to a store has come ‘outbound’ from a depot)
- [Inbound] Depot Service is also referred to as [inbound] Supplier Service Level (representing the movement of items from supplier to depot)
- Planned Distribution is called Ranging (Flag), Store Listing etc.
What data grains are available in free supermarket data?
All of the ‘Big Four’ provide data at the following grains (follow this link for an explanation of data grain):
- Day x Item
– aggregate store metrics (sales, waste, stock, availability etc.) - Day x Item x Depot
– depot metrics (stock, inbound service, outbound service etc.) - Week x Item
– weekly summary of combined store and depot metrics
Many also provide:
- Day x Item x Store
– individual store metrics (sales, waste, stock, availability etc.)
In addition, most provide reference data for the key dimensions of their data:
- Store – reference data about stores, including type, format, location etc.
- Item – reference data about items, including category, pack size etc.
- Time – a reference calendar defining week number, accounting/promotional periods etc.
How can I collect data from the retailer portals?
If you are happy with infrequent high-grain data (e.g. Week x Item) then you can simply download an appropriate report from one or more retailer portal(s) every time you need it.
Running weekly reports is relatively quick and easy, although retailer portals are notoriously busy on Monday mornings and best avoided if you value your time! Many account managers will leave their weekly analysis until Monday afternoon or evening, when downloading last week’s sales report from each retailer is a little less stressful.
If you want to collect low-grain data – especially if you want to collect multiple metrics, at different levels of grain, on a daily basis – then you will probably want to automate report generation. Some of the retailer portals allow you to schedule reports that you can receive by email, others will require you to use some form of ‘software robot’ to login, run reports and download the resulting data files.
Here is an illustrative list of the retailer portals and their connectivity with our SKUtrak platform.
| Retailer | Portal | Login Link(s) | SKUtrak Compatible |
| Asda | RetailLink DSS Future Supplier ADR |
https://retaillink.login.wal-mart.com/ | YesTBC |
| Co-op | Unify SKUtrak |
https://advantage.eu.iriworldwide.com/unify-coop/index.html app.skutrak.com |
N/A Yes |
| Morrisons | Supplier Data Hub SKUtrak |
https://data-supplierdatahub-prd.firebaseapp.com/login app.skutrak.com |
N/A Yes |
| Sainsbury’s | SupplyHub | https://advantage.eu.iriworldwide.com/unify-sainsburys/ | Yes |
| Tesco | Tesco Partner ToolkitTesco Connect | https://partnerstoolkit.tesco.com/https://supplychain.tesco.com/ | Yes No |
| Waitrose | Connect | http://waitroseconnect.co.uk/ | Yes |
| Ocado | Beet | https://www.beet-insight.com/ | Coming Soon |
| Aldi | Edge | https://forecast.the-edge.io/ | Coming Soon |
| Amazon | Vendor Central | https://vendorcentral.amazon.co.uk/ | Coming Soon |
| Walmart | RetailLinkLuminate | https://retaillink.login.wal-mart.com/ https://www.walmartluminate.com/ |
Yes Yes |
| ITG Multiples | Retail Spotlight | https://www.retailspotlight.co.uk/ | Yes |
Where should I store supermarket data so that I can analyse it?
If you are collecting very high-grain data you will be able to store it in a spreadsheet, simply adding new data each day, or week, as you collect it. If you are collecting low-grain data on a daily basis then you will find it much more reliable, and cost-effective, to store the data in a database – anything from a simple key-value store (like MongoDB, Cosmos DB, DynamoDB, Firestore etc.) to a fully-formed data platform (like BigQuery, Databricks, Snowflake etc.).
Loading data into your preferred database requires careful consideration. Simple key-value stores allow you the flexibility of storing anything and everything in the format in which you receive it; this makes storage very simple but also requires your ‘readers’ (data engineers, analysts, data scientists, end-users, business systems, etc.) to understand the data source in detail.
Many organisations have achieved impressive results launching a key-value-based DSR very quickly, and developing end-user solutions over the top of it, only to discover that every extension with new data from new sources adds to an exponential data management/maintenance/explanation overhead.
Most large-scale data initiatives will require some form of standardisation, where source data is transformed into a retailer-independent format that allows all downstream ‘readers’ to access and interpret the data as if it came from a single source. Such data transformation, alignment and enrichment is normally the preserve of a demand signal repository – a platform designed to manage many different sources of demand data (from supermarkets and beyond) as a fully-managed service.