Small nuances and discrepancies in like-item prices are very common in the foodservice industry; this is often the result of two pricing models: cost-plus and value-based. These strategies, which have been used for years across the industry, do not fully allow for the integration of consumer behavior data that is now so much more accessible to operators and so relevant to pricing menu items. While the old methods are by no means incorrect, it is important to stay ahead of the curve and innovate at the same pace as the industry; not taking massive amount of data into consideration may be causing operators to miss out on opportunities to increase check averages.
Systems can be built to leverage large amounts of data and new technology to understand purchase behavior. Amazon has created algorithmic systems that alter millions of prices multiple times throughout the day based on e-commerce purchase behavior based off of region, time of day, aggregate consumer behavior and individual consumer behavior. Amazon is an example of how sophisticated pricing systems can be, and while the foodservice industry might not need as extreme of systems, it could definitely use an update that could borrow similar strategies.
QSR Magazine will be publishing a series of articles that explore alternative pricing strategies that can be applied to the industry using hypothetical restaurants with menu items and prices. The goal by the end of the series is to “determine quality inputs, analyze the data, optimize prices based off that data, and then do it all over again with a different set of inputs.” To read more about enhancing pricing strategies and to follow the series, click here
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