This tool helps determine the responsiveness of the quantity demanded of one good to a change in the price of another. For example, if the price of coffee rises, this tool could predict the change in demand for tea. It works by calculating the percentage change in the quantity demanded of one good divided by the percentage change in the price of the other good. A positive result suggests substitute goods, while a negative result suggests complementary goods.
Understanding the relationship between product pricing and consumer behavior is vital for businesses. This metric provides insights into market dynamics, enabling better pricing strategies, product development decisions, and competitive analysis. Historically, this type of analysis has become increasingly sophisticated with advances in data collection and computational power. This has led to more refined market models and more accurate predictions of consumer reactions to market shifts.
