Case – Item Availability & Saleability

Over 0.5%pts of sustained sales increase, from analysing every SKU, every hour, to direct store staff to fix issues immediately.


In 2008 the UK banner of a global retailer was spending more than £1m annually, undertaking an inefficient manual audit process to measure product availability on shelf.

From a total of approximately 30,000 products, only a fixed list of top selling items were checked weekly, accounting for less than 1% of the total range. This process was also open to human error, adding further variance to an limited availability measure, which didn’t correlate with sales performance or independent evaluation.



Working with the retailer, we brought our experience from the supplier’s perspective, where we already provided a product to help brands maintain shelf presence in store. By utilising granular item level sales data direct from the retailer, we evolved our solution, to track all items in all stores, during every hour of trading.

We refined our proprietary algorithms to calculate an expected sales pattern for every item, considering inputs such as the store, the time and day, and other external factors which could influence sales. When the actual sales of products deviated from their expectation beyond a defined probability level and other comparative conditions were fulfilled, alerts are automatically generated, prioritised and sent to store staff to take immediate action and recoup sales.



Within the first year of operation, the retailer moved from third position to first, on the independent industry evaluation for product availability. This was coupled with a continued positive sales increase, measured initially in excess of 0.5%.

Our ongoing relationship has enabled significant evolution of our product, to embrace changing environments, such as alerts initially being pushed directly to store staff via reports, then email, handheld devices and now a bespoke device agnostic mobile app which provides alerts within the day for instant benefit.

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