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A Healthcare company supplying products to grocery retailers wanted to understand how price changes on leading SKUs affected sales performance.
The aim was to understand whether the category could absorb future price rises to help drive profit. The client needed the results quickly, and therefore did not wish to invest in an econometrics study which would be more time consuming and costly to deliver. Instead, the client wanted quick results to help form the basis for internal discussions, and determine whether a further “deep dive” would be required.
As well as understanding whether price changes to their own SKUs affected sales, it was important to establish whether relative price relationships exist with competitor SKUs. Changes in distribution levels, investment in both Above-The-Line (ATL) and Below-The-Line (BTL) activity, macroeconomic factors (e.g. seasonality), are all factors that would also need to be accounted for to tease out the impact of price on sales as cleanly as possible.
Adding to the complexity was the time period to be analysed; this coincided with the series of lockdowns that came into force due to the COVID pandemic.
From the data available, a bespoke approach was devised for the client that analysed the sales performance of leading SKUs during a “base” period of time (i.e. where prices and activity were stable), and the change in performance during the “activity” period of time (i.e. where all factors largely remained stable, with the exception of price). This approach is similar to a “test and learn” analysis that allows for as many factors to be controlled for across the two time periods, with the one factor (price) the only metric changing to establish its relationship to sales.
The analysis conducted showed that, while historical increases in price affected unit sales, value sales remained largely stable across the grocery retailers analysed for the leading SKUs, indicating that the client could improve profit levels if the right conditions could be agreed with the retailer. However, it was important to note that this situation only held true when price increases did not breach perceived consumer price points, where unit sales did fall more substantially. This would need to be analysed further by the client to understand whether it was beneficial to increase prices beyond perceived price thresholds.
The analysis also flagged that certain relative price relationships did exist between the client’s own SKUs, and with key competitors, therefore caution must be taken if price increases are implemented that may switch customers and their sales to rival products.