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elm is designed to make retailer data easier to access, easier to understand and easier to act on, without relying on spreadsheets.
What is elm?
elm is a retail data and forecasting platform that helps brands understand how their products are performing across major UK retailers. elm connects directly to official retailer EPOS and reporting portals, such as Tesco Toolkit, Sainsbury’s Circana, Asda Data Reporting Hub, Morrisons Supplier Data Hub, Co-op Circana Unify+, Waitrose Connect and Amazon Seller and Vendor Central, and brings that data into one consistent, easy-to-use platform. Instead of switching between portals or manually exporting files, teams use elm to monitor metrics such as sales, distribution, availability, stock and service levels in one place.
What problem does elm solve for brands?
Retail data is often fragmented, inconsistent and time-consuming to work with. Each retailer portal presents data differently, uses different definitions and updates on different schedules.elm solves this by centralising retailer EPOS data into a single platform and standardising key metrics like rate of sale (ROS), availability and stock. This allows commercial, sales, category, marketing and supply chain teams to spend less time building reports and more time understanding performance and making decisions.
Which retailers does elm connect to?
elm supports direct connections to the UK’s major grocery and ecommerce retailers. These include Tesco via Tesco Toolkit, Sainsbury’s via Circana, Asda via the Asda Data Reporting Hub, Morrisons via the Supplier Data Hub, Co-op via Circana / Unify, Waitrose via Waitrose Connect and Amazon via Amazon Seller and Vendor Central. All data pulled into elm originates from these official retailer systems, so figures align closely with what buyers and internal retailer teams see.
What data does elm pull from retailer EPOS portals?
elm pulls the most commercially relevant data available from each retailer portal. This typically includes daily and weekly sales by product, units sold, revenue, store distribution, availability, stock in store, stock in depot and service level metrics. For example, elm pulls store and depot stock, supplier and depot service levels and wastage data from Tesco Toolkit and Morrisons Supplier Data Hub, while Asda Data Reporting Hub provides detailed daily and weekly store-level sales and stock information. The exact datasets available can vary by retailer, but elm is designed to surface consistent, decision-ready insights across all accounts.
How often does retail data update in elm?
Data refresh timing depends on the retailer, but most EPOS connections update daily, with some weekly datasets refreshing on Mondays. For retailers such as Tesco, Sainsbury’s, Morrisons and Waitrose, daily sales data is typically available by mid-morning once the retailer portal updates. Some retailers, such as Asda and Co-op, require a manual refresh step due to two-factor authentication, which elm clearly flags within the platform. elm automatically checks for new data and updates dashboards as soon as it becomes available.
How much historical data can I see when I connect a retailer?
When you first connect a retailer to elm, historical data is pulled based on what the retailer portal allows. This can be up to two years for retailers such as Tesco, Asda, Co-op and Morrisons. Daily sales history may be shorter than weekly data, depending on the retailer. If you already have older historical EPOS data stored internally, elm can also help append this so you can analyse longer-term trends in one place.
What metrics does elm track?
elm focuses on the metrics that commercial teams and buyers actually use. Sales metrics include revenue (£RSV), units sold and average selling price (ASP) where available. Performance metrics include rate of sale (ROS), scanning ROS and ranged ROS. Distribution metrics include stores ranged, stores selling and stocking points. Supply chain metrics include stock in store, stock in depot, supplier service level, depot service level and wastage. All metrics are clearly defined and calculated consistently, even when retailers report data differently, across different weekly start dates.
What is rate of sale (ROS) and how does elm calculate it?
Rate of sale (ROS) measures how well a product is selling in the stores where it is stocked. elm calculates “true ROS” wherever store-level data is available, using units sold divided by the number of stores holding stock in a given period. This provides a more accurate view of performance than high-level averages and helps teams understand whether sales issues are driven by demand, availability or distribution. elm also supports scanning ROS and ranged ROS, reflecting how buyers often review performance.
Can elm help with forecasting and planning?
Yes. elm has its own bespoke 'predictive forecasting' algorithm, which looks at historical EPOS trends, seasonality dips, promotional cycles, and predicts a forecast a year into the future. elm also allows brands to upload forecasts directly into the platform and compare them against actual EPOS performance. This helps teams identify gaps between forecast and reality, adjust plans earlier and improve future forecasting accuracy. Forecasting sits alongside live retailer data, making elm useful not just for reporting but for forward planning and decision-making. elm also has its own bespoke 'predictive forecasting' algorithm, which looks at historical EPOS trends, seasonality dips, promotional cycles, and predicts a forecast a year into the future.
What happens when new products launch or SKUs are delisted?
New SKUs typically pull through automatically once they appear in the retailer portal. If a product is delisted, elm continues to show its historical sales data to ensure reporting accuracy. Brands can optionally mark SKUs as delisted within elm to keep dashboards clean and prevent delisted items from skewing average metrics such as ROS.
Do I need technical or data expertise to use elm?
No. elm is designed for commercial, sales and supply chain teams rather than data specialists. Dashboards are visual, metrics are clearly labelled and most users can start exploring performance immediately. elm removes the need to understand the nuances of each retailer portal, while still preserving the integrity of the underlying data.
Who typically uses elm within a business?
elm is used by FMCG and consumer brands across sales, account management, marketing, category, and supply chain teams.
How is elm different from logging directly into retailer portals?
Retailer portals such as Tesco Toolkit, Sainsbury’s Circana and Asda Data Reporting Hub are essential, but they are siloed and inconsistent, meaning NAMs spend hours consolidating the data from multiple spreadsheets. elm brings this data together, standardises definitions and makes it easier to compare performance across retailers. Teams spend less time downloading files and reconciling numbers, and more time understanding trends and taking action.
How can elm be used for field sales?
Through the 'Syndicated Actions' tool; elm utilises EPOS store level data to identify 'action' stores. These action stores are assigned a call value (the estimated return on investment of a field sales visit) to rank them by priority. Based on your budget (there is no minimum spend) elm then automatically sends a field sales agent in from our partner agency, Expd8, the next day. You can then view a granular store level ROS analysis of your visits the following week.
Can elm be used for marketing teams?
elm has its own marketing and brand tracking tool called 'BrandHealth', which allows FMCG challenger brands to track and monitor their brand performance and sentiment across time. It has two main components: 'Monthly Dips' and 'Quarterly Deep Dives'. It is the only brand tracking tool bespoke to the FMCG industry.
How do brands get started with elm?
Most brands can connect their first retailer by adding their portal access details within elm. Once verified, data begins flowing automatically. For brands exploring EPOS reporting or forecasting tools, elm provides a practical way to move from raw retailer data to clear, actionable insight.
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