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Using Natural Experiments to Understand the Impact of Price Increases

The Company

A leading national restaurant chain

The Challenge

With commodity cost increases looming, the client was deliberating whether or not to raise prices on certain menu items. Based on previous analysis, management thought they could profitably increase the price of appetizers but wanted to validate these findings before taking price across the network.

The Solution

APT ran multiple years of the client’s data through the “Natural Experiment Finder” module of APT software to find instances in which some restaurants increased price of the appetizers, while also identifying control restaurants that did not.

APT software showed that increasing the price of appetizers led to a significant decrease in appetizer unit volume. More importantly, the client discovered that as guests noticed the increased prices, total restaurant traffic began to decline and eventually leveled out to a steady-state that was significantly lower than before the increases. Overall, increasing prices had directly caused millions of dollars in lost sales and profits. However, by de-averaging the results, the client found that the price increases led to a minimal decrease in transactions in select locations. APT then built a predictive model to target rollout of the appetizer price increase to a small subset of the network scientifically predicted to respond profitably.

The Results

Based on these findings, the client decided not to increase prices on their signature appetizer across the entire chain, preventing tens of millions of dollars in lost profits.
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