Final answer:
The useful engineered feature in predicting a grocery store's revenue is the total revenue, which can be calculated using the total number of items sold and the average price per item. Analyzing the price elasticity of demand is also important.
Step-by-step explanation:
The useful engineered feature in predicting a grocery store's revenue would be the total revenue (c). By calculating the total revenue, which is the product of the total number of items sold (a) and the average price per item (b), the grocery store can gain insights into its overall performance and make informed decisions regarding pricing and inventory management.
For example, if the total revenue is decreasing, the store might consider adjusting its pricing strategy or exploring new product offerings. Additionally, analyzing the price elasticity of demand (d) can help the store understand how changes in price impact the quantity of items sold and make data-driven decisions to maximize revenue.
However, price elasticity of demand could also be an insightful feature, especially if the price can be strategically modified to maximize revenue. If the elasticity of demand is high (greater than 1), a decrease in price is advised as it could lead to a proportionally larger increase in quantity sold, increasing total revenue. Conversely, if the elasticity is less than 1, an increase in price might be better as it would lead to higher total revenue despite a smaller decrease in quantity sold. If the elasticity is exactly 1, revenue is maximized at the current price, so no change is recommended.